Brian Kernighan was a member of the original group of Unix developers, the creator of several fundamental Unix programs, and the co-author of classic books like "The C Programming Language" and "The Unix Programming Environment."

    However, Python’s unique strengths, charms, and expressiveness can be hard to grasp, and there are hidden pitfalls that can easily trip you up. This second edition of Effective Python will help you master a truly “Pythonic” approach to programming, harnessing Python’s full power to write exceptionally robust and well-performing code. Using the concise, scenario-driven style pioneered in Scott Meyers’ best-selling Effective C++, Brett Slatkin brings together 90 Python best practices, tips, and shortcuts, and explains them with realistic code examples so that you can embrace Python with confidence. Drawing on years of experience building Python infrastructure at Google, Slatkin uncovers little-known quirks and idioms that powerfully impact code behavior and performance. You’ll understand the best way to accomplish key tasks so you can write code that’s easier to understand, maintain, and improve. In addition to even more advice, this new edition substantially revises all items from the first edition to reflect how best practices have evolved. Key features include 30 new actionable guidelines for all major areas of Python Detailed explanations and examples of statements, expressions, and built-in types Best practices for writing functions that clarify intention, promote reuse, and avoid bugs Better techniques and idioms for using comprehensions and generator functions Coverage of how to accurately express behaviors with classes and interfaces Guidance on how to avoid pitfalls with metaclasses and dynamic attributes More efficient and clear approaches to concurrency and parallelism Solutions for optimizing and hardening to maximize performance and quality Techniques and built-in modules that aid in debugging and testing Tools and best practices for collaborative development   Effective Python will prepare growing programmers to make a big impact using Python.

    They are built with the objective of providing assessment, review, and practice to help ensure you are fully prepared for your certification exam. This book, combined with the CCNA 200-301 Official Cert Guide Volume 2, cover all of exam topics on the CCNA 200-301 exam. CCNA 200-301 Official Cert Guide, Volume 1 presents you with an organized test-preparation routine using proven series elements and techniques. "Do I Know This Already?" quizzes open each chapter and enable you to decide how much time you need to spend on each section. Exam topic lists make referencing easy. Chapter-ending Exam Preparation Tasks help you drill on key concepts you must know thoroughly. - Master Cisco CCNA 200-301 exam topics - Assess your knowledge with chapter-opening quizzes - Review key concepts with exam preparation tasks - Practice with realistic exam questions in the practice test software CCNA 200-301 Official Cert Guide, Volume 1 from Cisco Press enables you to succeed on the exam the first time and is the only self-study resource approved by Cisco. Best-selling author and expert instructor Wendell Odom shares preparation hints and test-taking tips, helping you identify areas of weakness and improve both your conceptual knowledge and hands-on skills. This complete study package includes - A test-preparation routine proven to help you pass the exams - Do I Know This Already? quizzes, which enable you to decide how much time you need to spend on each section - Chapter-ending and part-ending exercises, which help you drill on key concepts you must know thoroughly -The powerful Pearson Test Prep Practice Test software, complete with hundreds of well-reviewed, exam-realistic questions, customization options, and detailed performance reports - A free copy of the CCNA 200-301 Volume 1 Network Simulator Lite software, complete with meaningful lab exercises that help you hone your hands-on skills with the command-line interface for routers and switches - Links to a series of hands-on config labs developed by the author - Online, interactive practice exercises that help you hone your knowledge - More than 90 minutes of video mentoring from the author - A final preparation chapter, which guides you through tools and resources to help you craft your review and test-taking strategies - Study plan suggestions and templates to help you organize and optimize your study time Well regarded for its level of detail, study plans, assessment features, challenging review questions and exercises, video instruction, and hands-on labs, this official study guide helps you master the concepts and techniques that ensure your exam success. The CCNA 200-301 Official Cert Guide, Volume 1, combined with CCNA 200-301 Official Cert Guide, Volume 2, walk you through all the exam topics found in the Cisco 200-301 exam. Topics covered in Volume 1 include: - Networking fundamentals - Implementing Ethernet LANs - Implementing VLANs and STP - IPv4 addressing - IPv4 routing - OSPF - IPv6 - Wireless LANs Companion Website The companion website contains more than 300 unique practice exam questions, CCNA Network Simulator Lite software, online practice exercises, and 90 minutes of video training. Includes Exclusive Offers For Up to 70% Off Video Training, Practice Tests, and more Also available from Cisco Press for CCNA study is the CCNA 200-301 Official Cert Guide, Volume 1 Premium Edition eBook and Practice Test. This digital-only certification preparation product combines an eBook with enhanced Pearson Test Prep Practice Test. This integrated learning package - Enables you to focus on individual topic areas or take complete, timed exams - Includes direct links from each question to detailed tutorials to help you understand the concepts behind the questions - Provides unique sets of exam-realistic practice questions - Tracks your performance and provides feedback on a module-by-module basis, laying out a complete assessment of your knowledge to help you focus your study where it is needed most In addition to the wealth of updated content, this new edition includes a series of free hands-on exercises to help you master several real-world configuration and troubleshooting activities. These exercises can be performed on the CCNA 200-301 Network Simulator Lite, Volume 1 software included for free on the companion website that accompanies this book. This software, which simulates the experience of working on actual Cisco routers and switches, contains the following 22 free lab exercises, covering topics in Part II and Part III, the first hands-on configuration sections of the book: 1. Configuring Local Usernames 2. Configuring Hostnames 3. Interface Status I 4. Interface Status II 5. Interface Status III 6. Interface Status IV 7. Configuring Switch IP Settings 8. Switch IP Address 9. Switch IP Connectivity I 10. Switch CLI Configuration Process I 11. Switch CLI Configuration Process II 12. Switch CLI Exec Mode 13. Setting Switch Passwords 14. Interface Settings I 15. Interface Settings II 16. Interface Settings III 17. Switch Forwarding I 18. Switch Security I 19. Switch Interfaces and Forwarding Configuration Scenario 20. Configuring VLANs Configuration Scenario 21. VLAN Troubleshooting

    I'm a retired SEAL. And an infuriatingly wild-spirited woman is no challenge.   The demons from my past are back. And my little girl's life is at stake.  I'll protect them both. But I can't let it go further than that. Because doing what I really want to Candace is both a distraction... And downright un-neighborly.        This scorching hot single dad next door romance offers an unforgettable HEA and a FULL-LENGTH standalone reading experience guaranteed to leave you panting for more. Snag your copy today.

    This hands-on book helps you learn the Kotlin language with a unique method that goes beyond syntax and how-to manuals and teaches you how to think like a great Kotlin developer. You'll learn everything from language fundamentals to collections, generics, lambdas, and higher-order functions. Along the way, you'll get to play with both object-oriented and functional programming. If you want to really understand Kotlin, this is the book for you.Why does this book look so different?Based on the latest research in cognitive science and learning theory, Head First Kotlin uses a visually rich format to engage your mind rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multisensory learning experience is designed for the way your brain really works.

    This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach.Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use.Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow LiteDevelop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google CoralExplore fun projects, from Silicon Valley's Not Hotdog app to 40+ industry case studiesSimulate an autonomous car in a video game environment and build a miniature version with reinforcement learningUse transfer learning to train models in minutesDiscover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users

    When you build your own computer, you are in charge of what components are going to be used so you know that it will perform the way you want it to.The goal of this book is to help you choose the parts (components) for your new computer so you can end up with a computer that does what you want it to do. Then you will be taken through the build process with step by step instructions and illustrations making it easy to get your new computer up and running in no time. Finally you will be guided through the process of installing an operating system on your computer so you can start enjoying your work. The chapters in the book cover the following topics: Chapter 1 – Why Build Your Own Computer?Chapter 2 – Choosing Components Chapter 3 – Planning Your BuildChapter 4 – Putting the Pieces TogetherChapter 5 – Initial Power UpChapter 6 – Installing Your Operating System About the Author James Bernstein has been working with various companies in the IT field since 2000, managing technologies such as SAN and NAS storage, VMware, backups, Windows Servers, Active Directory, DNS, DHCP, Networking, Microsoft Office, Exchange, and more.He has obtained certifications from Microsoft, VMware, CompTIA, ShoreTel, and SNIA, and continues to strive to learn new technologies to further his knowledge on a variety of subjects.He is also the founder of the website OnlineComputerTips.com, which offers its readers valuable information on topics such as Windows, networking, hardware, software, and troubleshooting. Jim writes much of the content himself and adds new content on a regular basis. The site was started in 2005 and is still going strong today.

    Recent advances in the field have shown how it's possible to teach a machine to excel at human endeavors--such as drawing, composing music, and completing tasks--by generating an understanding of how its actions affect its environment.With this practical book, machine learning engineers and data scientists will learn how to recreate some of the most famous examples of generative deep learning models, such as variational autoencoders and generative adversarial networks (GANs). You'll also learn how to apply the techniques to your own datasets.David Foster, cofounder of Applied Data Science, demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to the most cutting-edge algorithms in the field. Through tips and tricks, you'll learn how to make your models learn more efficiently and become more creative.Get a fundamental overview of deep learningLearn about libraries such as Keras and TensorFlowDiscover how variational autoencoders workGet practical examples of generative adversarial networks (GANs)Understand how autoregressive generative models functionApply generative models within a reinforcement learning setting to accomplish tasks

    In reality, the project fell short in many ways--starting with the hand crank, which never materialized. Yet the project remained charismatic to many who were captivated by its claims of access to educational opportunities previously out of reach. Behind its promises, OLPC, like many technology projects that make similarly grand claims, had a fundamentally flawed vision of who the computer was made for and what role technology should play in learning.Drawing on fifty years of history and a seven-month study of a model OLPC project in Paraguay, Ames reveals that the laptops were not only frustrating to use, easy to break, and hard to repair, they were designed for "technically precocious boys"--idealized younger versions of the developers themselves--rather than the children who were actually using them. The Charisma Machine offers a cautionary tale about the allure of technology hype and the problems that result when utopian dreams drive technology development.

    Dream Phaze is about the inception of engineered dreams and the evolution of indulgence. Set at the crossroads of alternative realities in the near future, it plunges into a world where every human desire, no matter how heroic or evil, can be fulfilled…

     Real-World Bug Hunting is the premier field guide to finding software bugs. Whether you're a cyber-security beginner who wants to make the internet safer or a seasoned developer who wants to write secure code, ethical hacker Peter Yaworski will show you how it's done.You'll learn about the most common types of bugs like cross-site scripting, insecure direct object references, and server-side request forgery. Using real-life case studies of rewarded vulnerabilities from applications like Twitter, Facebook, Google, and Uber, you'll see how hackers manage to invoke race conditions while transferring money, use URL parameter to cause users to like unintended tweets, and more.Each chapter introduces a vulnerability type accompanied by a series of actual reported bug bounties. The book's collection of tales from the field will teach you how attackers trick users into giving away their sensitive information and how sites may reveal their vulnerabilities to savvy users. You'll even learn how you could turn your challenging new hobby into a successful career. You'll learn:- How the internet works and basic web hacking concepts - How attackers compromise websites - How to identify functionality commonly associated with vulnerabilities - How to find bug bounty programs and submit effective vulnerability reportsReal-World Bug Hunting is a fascinating soup-to-nuts primer on web security vulnerabilities, filled with stories from the trenches and practical wisdom. With your new understanding of site security and weaknesses, you can help make the web a safer place--and profit while you're at it.

    We're talking hard stuff - attacks buried deep in a machine's boot process or UEFI firmware that keep malware analysts up late at night.Security experts Alex Matrosov, Eugene Rodionov, and Sergey Bratus share the knowledge they've gained over years of professional research. With these field notes, you'll trace malware evolution from rootkits like TDL3 to present day UEFI implants and examine how these malware infect the system, persist through reboot, and evade security software. While you inspect real malware under the microscope, you'll learn:-The details of the Windows boot process, from 32-bit to 64-bit and UEFI, and where it's vulnerable. -Boot process security mechanisms like Secure Boot, the kernel-mode signing policy include some details about recent technologies like Virtual Secure Mode (VSM) and Device Guard. -The reverse engineering and forensic approaches for real malware discovered in the wild, including bootkits like Rovnix/Carberp, Gapz, TDL4 and the infamous rootkits TDL3 and Festi. -How to perform boot process dynamic analysis using emulation and virtualization-Modern BIOS-based rootkits and implants with directions for forensic analysisCybercrime syndicates and malicious actors keep pushing the envelope, writing ever more persistent and covert attacks. But the game is not lost. Explore the cutting edge of malware analysis with Rootkits and Bootkits.Covers boot processes for Windows 32-bit and 64-bit operating systems.

    But applications that create realistic images, natural sentences and paragraphs, or native-quality translations have proven elusive. Generative Adversarial Networks, or GANs, offer a promising solution to these challenges by pairing two competing neural networks' one that generates content and the other that rejects samples that are of poor quality. GANs in Action: Deep learning with Generative Adversarial Networks teaches you how to build and train your own generative adversarial networks. First, you'll get an introduction to generative modelling and how GANs work, along with an overview of their potential uses. Then, you'll start building your own simple adversarial system, as you explore the foundation of GAN architecture: the generator and discriminator networks.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

    By using the PropEr framework in both Erlang and Elixir, this book teaches you how to automatically generate test cases, test stateful programs, and change how you design your software for more principled and reliable approaches. You will be able to better explore the problem space, validate the assumptions you make when coming up with program behavior, and expose unexpected weaknesses in your design. PropEr will even show you how to reproduce the bugs it found. With this book, you will be writing efficient property-based tests in no time.Most tests only demonstrate that the code behaves how the developer expected it to behave, and therefore carry the same blind spots as their authors when special conditions or edge cases show up. Learn how to see things differently with property tests written in PropEr.Start with the basics of property tests, such as writing stateless properties, and using the default generators to generate test cases automatically. More importantly, learn how to think in properties. Improve your properties, write custom data generators, and discover what your code can or cannot do. Learn when to use property tests and when to stick with example tests with real-world sample projects. Explore various testing approaches to find the one that's best for your code. Shrink failing test cases to their simpler expression to highlight exactly what breaks in your code, and generate highly relevant data through targeted properties. Uncover the trickiest bugs you can think of with nearly no code at all with two special types of properties based on state transitions and finite state machines.Write Erlang and Elixir properties that generate the most effective tests you'll see, whether they are unit tests or complex integration and system tests.What You NeedBasic knowledge of Erlang, optionally ElixirFor Erlang tests: Erlang/OTP >= 20.0, with Rebar >= 3.4.0For Elixir tests: Erlang/OTP >= 20.0, Elixir >= 1.5.0

    The awesome Linux zines you love, now as a fancy box set!Ever wished you could spy on your computer with a handy incantation or bewitch your programs to debug themselves--now you can by becoming a Linux wizard! Okay, reading these zines won't actually make you a wizard, but you'll sure feel like one after you learn some neat Linux tricks.With this collected edition of Julia Evans's wildly popular Linux zines, you'll get super awesome repackaged versions of the zines like:* Networking, ACK! to learn how cat pics teleport from a server to your laptop through the magic of networking* So You Want to be a Wizard, which teaches you how to become a certified programming wizard * Linux Comics to explore the nitty gritty of how IPv6, floating point, and CPU scheduling work* Let's Learn tcpdump! to dump all your network traffic right into your CLI* Linux debugging tools you'll love, so you can get the scoop on things like opensnoop, netcat, and netstat* Spying on Your Programs with strace lets you be a secret agent so you can see what programs your computer is (or isn't!) running* Profiling & Tracing with perf teaches you how much CPU your functions are usingThrough Julia's insatiable curiosity for all things technical, you'll view programming in a way you never have before--now on fancier paper!

    Games are an interactive medium, and this interplay between author, player and machine provides new and exciting ways to create and tell stories. In each essay, practitioners of this artform demonstrate how traditional storytelling tools such as characterization, world-building, theme, momentum and atmosphere can be adapted to full effect, using specific examples from their games. The reader will learn to construct narrative systems, write procedural dialog, and generate compelling characters with unique personalities and backstories.Key FeaturesIntroduces the differences between static/traditional game design and procedural game design Demonstrates how to solve or avoid common problems with procedural game design in a variety of concrete ways World's finest guide for how to begin thinking about procedural design

    Covers key concepts like confidentiality, integrity, and availability, then dives into practical applications of these ideas in the areas of operational, physical, network, application, and operating system security.Foundations of Information Security provides readers with fundamental knowledge of information security in both theoretical and practical aspects. Best selling author Jason Andress provides the basic knowledge needed to understand the key concepts of confidentiality, integrity, and availability, and then dives into practical applications of these ideas in the areas of operational, physical, network, application, and operating system security. Each chapter explores one main security concept, lists scenarios in which the concept is applicable, and discusses the implementation of that concept in detail, often by going over rival models or strategies. Readers will come away with a sense of what types of assets need protecting, what kinds of risks exist, and what kinds of defensive measures can be taken.

    Using traditional computing, even common desktop encryption could take decades for specialized 'crackers' to break and government and infrastructure-grade encryption would take billions of times longer. In light of these facts, it may seem that today's computer cryptography is a rock-solid way to safeguard everything from online passwords to the backbone of the entire internet. Unfortunately, many current cryptographic methods will soon be obsolete. In 2016, the National Institute of Standards and Technology (NIST) predicted that quantum computers will soon be able to break the most popular forms of public key cryptography. The encryption technologies we rely on every day--HTTPS, TLS, WiFi protection, VPNs, cryptocurrencies, PKI, digital certificates, smartcards, and most two-factor authentication--will be virtually useless. . . unless you prepare.Cryptography Apocalypse is a crucial resource for every IT and InfoSec professional for preparing for the coming quantum-computing revolution. Post-quantum crypto algorithms are already a reality, but implementation will take significant time and computing power. This practical guide helps IT leaders and implementers make the appropriate decisions today to meet the challenges of tomorrow. This important book:Gives a simple quantum mechanics primer Explains how quantum computing will break current cryptography Offers practical advice for preparing for a post-quantum world Presents the latest information on new cryptographic methods Describes the appropriate steps leaders must take to implement existing solutions to guard against quantum-computer security threats Cryptography Apocalypse: Preparing for the Day When Quantum Computing Breaks Today's Crypto is a must-have guide for anyone in the InfoSec world who needs to know if their security is ready for the day crypto break and how to fix it.

    With new features, language improvements, paradigms, and potential use cases appearing regularly, there’s never been a more exciting time to be a JavaScript developer. In The Joy of JavaScript, author and JavaScript expert Luis Atencio teaches you key design concepts that lead to clean, lean, modular, and easy-to-maintain code.

    Viktor Farcic interviews DevOps industries voices including Mike Kail, Greg Bledsoe, Jeff Sussna, James Turnbull, Kohsuke Kawaguchi, Liz Keogh, and more. Key Features Leading DevOps experts share their insights into modern DevOps practice Engage with the real-world challenges of putting DevOps to work Strengthen your DevOps practices now and prepare for future DevOps trends Book Description DevOps promises to break down silos, uniting organizations to deliver high quality output in a cross-functional way. In reality it often results in confusion and new silos: pockets of DevOps practitioners fight the status quo, senior decision-makers demand DevOps paint jobs without committing to true change. Even a clear definition of what DevOps is remains elusive.In DevOps Paradox, top DevOps consultants, industry leaders, and founders reveal their own approaches to all aspects of DevOps implementation and operation. Surround yourself with expert DevOps advisors. Viktor Farcic draws on experts from across the industry to discuss how to introduce DevOps to chaotic organizations, align incentives between teams, and make use of the latest tools and techniques.With each expert offering their own opinions on what DevOps is and how to make it work, you will be able to form your own informed view of the importance and value of DevOps as we enter a new decade. If you want to see how real DevOps experts address the challenges and resolve the paradoxes, this book is for you. What you will learn Expert opinions on: Introducing DevOps into real-world, chaotic business environments Deciding between adopting cutting edge tools or sticking with tried-and-tested methods Initiating necessary business change without positional power Managing and overcoming fear of change in DevOps implementations Anticipating future trends in DevOps and how to prepare for them Getting the most from Kubernetes, Docker, Puppet, Chef, and Ansible Creating the right incentives for DevOps success across an organization The impact of new techniques, such as Lambda, serverless, and schedulers, on DevOps practice Who this book is for Anybody interested in DevOps will gain a lot from this book. If you want to get beyond the simplistic ideals and engage with the deep challenges of putting DevOps to work in the real world, this book is for you. Table of Contents Jeff Sussna - Founder and CEO, Sussna Associates Damien Duportal - Træfik's Developer Advocate Kevin Behr - IT Strategist; Chief Scientific Officer, PraxisFlow Mike Kail - Chief Technology Officer, Everest.org James Turnbull - Chairman, Rethink Robotics Liz Keogh - Tech consultant Julian Simpson - Global IT Manager, Neo4j Andy Clemenko - Senior Solutions Engineer at Docker Chris Riley - Author and DevOps Analyst Adam Sandor - Cloud technology consultant Julia Biro - Site Reliability Engineer, Contentful Damon Edwards - Co-Founder and Chief Product Officer of Rundeck, Inc Kohsuke Kawaguchi - Chief Technology Officer, CloudBees Sean Hull - Cloud Architect Bret Fischer - Docker Captain, and Cloud SysAdmin Nirmal Mehta - Technology Consultant Greg Bledsoe - Agile

    This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You'll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way.Author Seth Weidman shows you how neural networks work using a first principles approach. You'll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you'll be set up for success on all future deep learning projects.This book provides:Extremely clear and thorough mental models--accompanied by working code examples and mathematical explanations--for understanding neural networksMethods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented frameworkWorking implementations and clear-cut explanations of convolutional and recurrent neural networksImplementation of these neural network concepts using the popular PyTorch framework

     Adobe Photoshop Classroom in a Book contains lessons that cover the basics and beyond, providing countless tips and techniques to help you become more productive with the program. You can follow the book from start to finish or choose only those lessons that interest you.Purchasing this book includes valuable online extras. Follow the instructions in the "Getting Started" section of the book to unlock access to: Downloadable lesson files you need to work through the projects in the bookWeb Edition containing the complete text of the bookWhat you need to use this book: Adobe Photoshop software, for either Windows or macOS. (Software not included.)Note: Classroom in a Book does not replace the documentation, support, updates, or any other benefits of being a registered owner of Adobe Photoshop software.

    This book walks you through the basics of the studio tool, provides tutorials for specific actions and creations, then explains how to use all of that knowledge to create your own unique game world! With detailed instructions, example screenshots, and simple explanations of what code to use and how to use it, this book is a must-have guide for any Roblox game designer!

    This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them.It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch.By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learn Learn various neural network architectures and its advancements in AI Master deep learning in Python by building and training neural network Master neural networks for regression and classification Discover convolutional neural networks for image recognition Learn sentiment analysis on textual data using Long Short-Term Memory Build and train a highly accurate facial recognition security system Who this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks. Table of Contents Machine Learning and Neural Networks 101 Predicting Diabetes with Multilayer Perceptrons Predicting Taxi Fares with Deep Feedforward Networks Cats Versus Dogs - Image Classification Using CNNs Removing Noise from Images Using Autoencoders Sentiment Analysis of Movie Reviews Using LSTM Implementing a Facial Recognition System with Neural Networks What’s Next?

    I want you to feel comfortable with all aspects of your watch in an environment that encourages you to learn painlessly at your own pace. My goal is to help you enjoy the wonder of discovering your Apple Watch. Along the way, I want to:  Teach you how to use all the features of your Apple Watch. I say “all.” As far as I know, I found every darned one of them, but don’t sue me if I missed one. Note: Details about the Compass app were not available at the time of publication. Demonstrate the cool and awe-inspiring features of the Apple Watch. These aren’t random tips and tricks. Rather, I have showcased them in a way that lets you find them while exploring a particular feature or topic. Help you find what you want, when you want it. The organized and detailed Table of Contents includes more than 200 topics. Skip around to your heart’s content. Inspire you with over 100 third-party apps. A few of the categories include entertainment, productivity, sports, photography, and games. We’ll also cover integration platforms like IFTTT, which opens up the possibility of unlimited applications. Focus on the engineering and Apple platforms behind the Apple Watch. The physical device includes the heart rate monitor, accelerometer, gyroscope, and Apple’s Force Touch technology. Behind the scenes, learn how Apple is partnering with businesses to extend their HealthKit, HomeKit, and GymKit platforms to enhance your experience for years to come. List 30 Common Troubleshooting and Maintenance Suggestions. While you can use your Apple Watch with watchOS 6 and later without your iPhone nearby, the Apple iPhone is an integral part of your day-to-day experience. In case you are new to Apple’s smartphone and iOS mobile operating system, I’ve included several topics covering the iPhone setup, screens, and gestures. Those topic headings have an asterisk and special formatting, so you can quickly skip them if you aren’t interested. As a final selling point, I make an intentional effort to avoid a few of my pet peeves – and those pertain to incomplete instructions. I frequently see directions such as “tap to go to settings,” but they leave novice users asking, “tap where?” In another example I read, the instructions mentioned a workout playlist and how to enable it – but assumed nothing went awry (and something ALWAYS goes awry). I intend to cover those bases for you. And if I do, by chance, make the mistake of omitting a critical detail anywhere in this book, know that I was probably distracted by my Apple Watch telling me to get moving or to breathe. I apologize ahead of time; it wasn’t intentional. Are you ready for the Apple Watch experience? Let’s get started.

    This book tells them how.It has been written by a professional search engine consultant. Richard Conway started his company, Pure SEO, in 2009 with just $200 to spend on a single web page. From there, mostly using digital marketing, he has expanded the business to four offices in New Zealand and Australia. Pure SEO has been listed by Deloitte in the fastest-growing 500 tech companies in the Asia Pacific region for the past five years.This practical guide cuts through the mis-information and sets the record straight on what actions you need to take, so searchers will find your product quickly and easily. It covers keywords, website content and structure, mobile search and optimisation, loading speed of your website and how that affects searches, planning content to make it easily searchable, tracking tools and much much more.With Australasian-focused statistics and insights, as well as advice about how these two markets differ, the book is an authoritative and accessible 'how to' resource.Case studies and Q&A sections provide real-life dos and don'ts. As well as actionable advice and 'red flags' to avoid, the book also looks ahead to consider the future of search marketing.

    And along the way, you’ll pick up some interesting insights into why Haskell looks and works the way it does. Get ready to go deep!

    This engaging and refreshingly different guide breaks down the skills into clear step-by-step chunks and explains the theory using brief easy-to-understand language. Rather than bamboozling readers with pages of mind-numbing technical jargon, this book includes 150 practical challenges, putting the power in the reader's hands. Through creating programs to solve these challenges the reader will quickly progress from mastering the basics to confidently using subroutines, a graphical user interface, and linking to external text, csv and SQL files. This book is perfect for anyone who wants to learn how to program with Python. In particular, students starting out in computer science and teachers who want to improve their confidence in Python will find here a set of ready-made challenges for classroom use.

    This book is your complete guide to how Git and GitHub work in a professional team environment.Divided into three parts - Version Control, Project Management and Teamwork - this book reveals what waits for you in the real world and how to resolve the problems you may run into. Once past the basics of Git, you'll see how to manage a software project, and finally how to utilize Git and GithHub to work effectively as a team.You'll examine how to plan, follow and execute a project with GitHub, and then apply those concepts to real-world situations. Workaround the pitfalls that most programmers fall into when driving a project with Git by using proven tactics to avoid them. You will also be taught the easiest and quickest ways to resolve merge conflicts.A lot of modern books on Git don't go into depth about non-technical topics. Beginning Git and GitHub will help you cover all the bases right at the start of your career.What You'll LearnReview basic and advanced concepts of GitApply Project Management skills using GitHubSolve conflicts or, ideally, avoid them altogetherUse advanced concepts for a more boosted workflowWho This book Is ForNew developers, developers that have never worked in a team environment before, developers with basic knowledge of Git or GitHub, or anyone who works with text documents.

    In particular, the Unity game engine has penetrated all scales of videogame development, from the large studio to the hobbyist bedroom, such that over half of all new videogames are reportedly being made with Unity. This book provides an urgently needed critical analysis of Unity as 'cultural software' that facilitates particular production workflows, design methodologies, and software literacies. Building on long-standing methods in media and cultural studies, and drawing on interviews with a range of videogame developers, Benjamin Nicoll and Brendan Keogh argue that Unity deploys a discourse of democratization to draw users into its 'circuits of cultural software'. For scholars of media production, software culture, and platform studies, this book provides a framework and language to better articulate the increasingly dominant role of software tools in cultural production. For videogame developers, educators, and students, it provides critical and historical grounding for a tool that is widely used yet rarely analysed from a cultural angle.

    You’ll be guided through a Docker journey, starting with the key concepts and simple examples of .NET Framework and .NET Core apps in Docker containers on Windows. Then you’ll learn how to use Docker to modernize the architecture and development of traditional ASP.NET and SQL Server apps.The examples show you how to break up legacy monolithic applications into distributed apps and deploy them to a clustered environment in the cloud, using the exact same artifacts you use to run them locally. You’ll see how to build a CI/CD pipeline which uses Docker to compile, package, test and deploy your applications. To help you move confidently to production, you’ll learn about Docker security, and the management and support options.The book finishes with guidance on getting started with Docker in your own projects. You’ll walk through some real-world case studies for Docker implementations, from small-scale on-premises apps to very large-scale apps running on Azure. What you will learn Understand key Docker concepts: images, containers, registries and swarms Run Docker on Windows 10, Windows Server 2019, and in the cloud Deploy and monitor distributed solutions across multiple Docker containers Run containers with high availability and failover with Docker Swarm Master security in-depth with the Docker platform, making your apps more secure Build a Continuous Deployment pipeline, running Jenkins and Git in Docker Debug applications running in Docker containers using Visual Studio Plan the adoption of Docker in your organization Who this book is for If you want to modernize an old monolithic application without rewriting it, smooth the deployment to production, or move to DevOps or the cloud, then Docker is the enabler for you. This book gives you a solid grounding in Docker so you can confidently approach all of these scenarios. Table of Contents Getting Started with Docker on Windows Packaging and Running Applications in Docker Containers Developing Dockerized .NET Framework and .NET Core Applications Sharing Images with Docker Registries Adopting Container-First Solution Design Organizing Distributed Solutions with Docker Compose Orchestrating Distributed Solutions with Docker Swarm Administering and Monitoring Dockerized Solutions Understanding the Security Risks and Benefits of Docker Powering a Continuous Deployment Pipeline with Docker Debugging and Instrumenting Application Containers Containerize What You Know - Guidance for Implementing Docker

    Tracing the origins of software to eighteenth-century French encyclopedists' step-by-step descriptions of how things were made in the workshops of artists and artisans, Sack shows that programming languages are the offspring of an effort to describe the mechanical arts in the language of the liberal arts.Sack offers a reading of the texts of computing--code, algorithms, and technical papers--that emphasizes continuity between prose and programs. He translates concepts and categories from the liberal and mechanical arts--including logic, rhetoric, grammar, learning, algorithm, language, and simulation--into terms of computer science and then considers their further translation into popular culture, where they circulate as forms of digital life. He considers, among other topics, the "arithmetization" of knowledge that presaged digitization; today's multitude of logics; the history of demonstration, from deduction to newer forms of persuasion; and the post-Chomsky absence of meaning in grammar. With The Software Arts, Sack invites artists and humanists to see how their ideas are at the root of software and invites computer scientists to envision themselves as artists and humanists.

    With the announcement of new ray tracing APIs and hardware to support them, developers can easily create real-time applications with ray tracing as a core component. As ray tracing on the GPU becomes faster, it will play a more central role in real-time rendering. Ray Tracing Gems provides key building blocks for developers of games, architectural applications, visualizations, and more. Experts in rendering share their knowledge by explaining everything from nitty-gritty techniques that will improve any ray tracer to mastery of the new capabilities of current and future hardware. What you'll learn:  The latest ray tracing techniques for developing real-time applications in multiple domains Guidance, advice, and best practices for rendering applications with Microsoft DirectX Raytracing (DXR) How to implement high-performance graphics for interactive visualizations, games, simulations, and more Who this book is for: Developers who are looking to leverage the latest APIs and GPU technology for real-time rendering and ray tracing  Students looking to learn about best practices in these areas Enthusiasts who want to understand and experiment with their new GPUs

    Easy to browse, C# 8.0 Pocket Reference is ideal as a quick source of information or as a guide to get you rapidly up to speed if you already know Java, C++, or an earlier C# version.All programs and code snippets are available as interactive samples in LINQPad. You can edit these samples and instantly see the results without needing to set up projects in Visual Studio. Written by the author of C# 7.0 in a Nutshell, this pocket reference covers C# 8.0 without skimping on detail, including: C# fundamentals and features new to C# 8.0 Advanced topics like operator overloading, type constraints, iterators, nullable types, operator lifting, lambda expressions, and closures LINQ: sequences, lazy execution, standard query operators, and query expressions Unsafe code and pointers, custom attributes, preprocessor directives, and XML documentation

    In Becoming an Ethical Hacker, investigative reporter Gary Rivlin offers an easy-to-digest primer on what white hat hacking is, how it began, and where it’s going, while providing vivid case studies illustrating how to become one of these “white hats” who specializes in ensuring the security of an organization’s information systems. He shows how companies pay these specialists to break into their protected systems and networks to test and assess their security. Readers will learn how these white hats use their skills to improve security by exposing vulnerabilities before malicious hackers can detect and exploit them. Weaving practical how-to advice with inspiring case studies, Rivlin provides concrete, practical steps anyone can take to pursue a career in the growing field of cybersecurity.

    If you can write some Python code, this book is for you, no matter how little college-level math you know. Principal instructor Mark E. Fenner relies on plain-English stories, pictures, and Python examples to communicate the ideas of machine learning.Mark begins by discussing machine learning and what it can do; introducing key mathematical and computational topics in an approachable manner; and walking you through the first steps in building, training, and evaluating learning systems. Step by step, you'll fill out the components of a practical learning system, broaden your toolbox, and explore some of the field's most sophisticated and exciting techniques. Whether you're a student, analyst, scientist, or hobbyist, this guide's insights will be applicable to every learning system you ever build or use. Understand machine learning algorithms, models, and core machine learning concepts Classify examples with classifiers, and quantify examples with regressors Realistically assess performance of machine learning systems Use feature engineering to smooth rough data into useful forms Chain multiple components into one system and tune its performance Apply machine learning techniques to images and text Connect the core concepts to neural networks and graphical models Leverage the Python scikit-learn library and other powerful tools Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

    This book presents computer programming as a key method for solving mathematical problems. This second edition of the well-received book has been extensively revised: All code is now written in Python version 3.6 (no longer version 2.7). In addition, the two first chapters of the previous edition have been extended and split up into five new chapters, thus expanding the introduction to programming from 50 to 150 pages. Throughout the book, the explanations provided are now more detailed, previous examples have been modified, and new sections, examples and exercises have been added. Also, a number of small errors have been corrected. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style employed is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows students to write simple programs for solving common mathematical problems with numerical methods in the context of engineering and science courses. The emphasis is on generic algorithms, clean program design, the use of functions, and automatic tests for verification.

    You'll learn how to learn all the necessary skills to truly become a Python virtuoso at the price of a nice lunch. In Python Programming: 21 Best Tips and Tricks, you're going to discover: The right mindset to approach writing computer programs that will help you write better codes Surefire methods to help you learn Python programming quickly and easily How to install Python and choose the best version to learn Python with as a beginner Step-by-step instructions to write your very first program in Python 7 powerful tips and tricks for beginner Python programmers that will fast-track your journey to becoming a master Setting up your coding environment to encourage learning and productivity ...and much more! Here's what you're going to discover in Python Programming For Beginners: Step-by-step instructions to download, install and set up the right Python version on your computer with instructions for Windows, Linux, and Mac A crash guide to Python basics to help you build a solid programming foundation Fundamental Python operations to get you up to speed with the language Best practices to help you write clean, understandable and flexible code when writing programs in Python Introduction to basic data types in Python—numbers, lists, tuples, sets, etc ...and tons more! Finally, here's a snippet of what you're going to learn in Python Data Science: Real-world use cases of Data Science and Python and why the use of modern data analysis tools can transform your organization or business 5 data science tips and tricks that every data scientist should absolutely know about How to get started collecting and analyzing data effectively with NumPy How to make learning Python for Data Science a breeze with the right Python packages How to practice your newfound skills with the Python language by performing basic data visualization ...and tons more! Whether you're completely new to the world of Python programming or you're a programmer looking to switch career tracks to the rapidly evolving field of data science and analytics, this special bundle is designed to help you hit the ground running with Python as soon as possible. Scroll to the top of the page and click the "Add to Cart" button to purchase today!

    

    By the end of this book, you will be able to write and read assembly code, mix assembly with higher level languages, know what AVX is, and a lot more than that. The code used in Beginning x64 Assembly Programming is kept as simple as possible, which means: no graphical user interfaces or whistles and bells or error checking. Adding all these nice features would distract your attention from the purpose: learning assembly language. The theory is limited to a strict minimum: a little bit on binary numbers, a short presentation of logical operators, and some limited linear algebra. And we stay far away from doing floating point conversions. The assembly code is presented in complete programs, so that you can test them on your computer, play with them, change them, break them. This book will also show you what tools can be used, how to use them, and the potential problems in those tools. It is not the intention to give you a comprehensive course on all of the assembly instructions, which is impossible in one book: look at the size of the Intel Manuals. Instead, the author will give you a taste of the main items, so that you will have an idea about what is going on. If you work through this book, you will acquire the knowledge to investigate certain domains more in detail on your own. The majority of the book is dedicated to assembly on Linux, because it is the easiest platform to learn assembly language. At the end the author provides a number of chapters to get you on your way with assembly on Windows. You will see that once you have Linux assembly under your belt, it is much easier to take on Windows assembly.This book should not be the first book you read on programming, if you have never programmed before, put this book aside for a while and learn some basics of programming with a higher-level language such as C.What You Will Learn Discover how a CPU and memory works Appreciate how a computer and operating system work together See how high-level language compilers generate machine language, and use that knowledge to write more efficient code Be better equipped to analyze bugs in your programs Get your program working, which is the fun part Investigate malware and take the necessary actions and precautions Who This Book Is ForProgrammers in high level languages. It is also for systems engineers and security engineers working for malware investigators.  Required knowledge: Linux, Windows, virtualization, and higher level programming languages (preferably C or C++).

     Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting-and lucrative!-careers in some of today's hottest programming fields. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.

    Written by 15-year-old technology phenom Tanmay Bakshi, the book is presented in an accessible style that makes learning easy and enjoyable. Tanmay Teaches Julia for Beginners: A Springboard to Machine Learning for All Ages clearly explains the basics of Julia programming and takes a look at cutting-edge machine learning applications. You will also discover how to interface your Julia apps with code written in Python.Inside, you'll learn to:- Set up and configure your Julia environment- Get up and running writing your own Julia apps- Define variables and use them in your programs- Use conditions, iterations, for-loops, and while-loops- Create, go through, and modify arrays- Build an app to manage things you lend and get back from your friends- Create and utilize dictionaries- Simplify maintenance of your code using functions- Apply functions on arrays and use functions recursively and generically- Understand and program basic machine learning apps

    Made using the same technology you find in a smartphone, the raspberry Pi is designed to help you learn coding, discover how computers work, and build your own amazing things. This book was written to show you just how easy it is to get started.Learn how to: * Set up your Raspberry Pi, install its operating system, and start using this tiny, fully functional computer.* Start coding projects, with step-by-step guides using the Scratch and python programming languages.* Experiment with connecting electronic components and have fun creating amazing projects.

    It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language.In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras.By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn Handle files and images, and explore various image processing techniques Explore image transformations, including translation, resizing, and cropping Gain insights into building histograms Brush up on contour detection, filtering, and drawing Work with Augmented Reality to build marker-based and markerless applications Work with the main machine learning algorithms in OpenCV Explore the deep learning Python libraries and OpenCV deep learning capabilities Create computer vision and deep learning web applications Who this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must. Table of Contents Setting up OpenCV Image basics in OpenCV Handling files and images Constructing basic shapes in OpenCV Image processing techniques Constructing and Building Histograms Thresholding techniques Contours Detection, filtering, and drawing Augmented reality and 3D Visualization Machine Learning and Deep Learning in OpenCV Face detection, tracking and recognition Introduction to deep learning Mobile and web computer vision with Python and OpenCV

    

    But the box is so minimalist, it just won't fit! New Apple users definitely need this book though. We go through the main gestures, icons, settings, apps. But this guide will also be useful for the fans of iPhones, since the XR is the latest iteration, furthermore it has the new iOS. We will look into the new possibilities of iOS, learn to live without the Home button, figure out the new photo modes, share a lot of secrets with our readers and of course tips on how to use this new miracle of tech! This guide contains detailed descriptions and instructions for the following sections: - Main Features Of IPhone XR And iOS12 - Setting up the iPhone XR - Basics - Learn basic gestures to interact with iPhone XR, Check out the meaning of status icons on iPhone XR, How to use the iPhone Home screen and open apps, Change your iPhone Settings - How to use various apps - App basics, App Store, Books, Camera, FaceTime, Files, Find My Friends, Find My iPhone location, iTunes, Safari, etc - Tricks and Tips on how to use the iPhone XR

    With this comprehensive guide, you’ll learn just how powerful the combination of C# and .NET can be. Author Ian Griffiths guides you through C# 8.0 fundamentals and techniques for building cloud, web, and desktop applications.Designed for experienced programmers, this book provides many code examples to help you work with the nuts and bolts of C#, such as generics, LINQ, and asynchronous programming features. You’ll get up to speed on .NET Core and the latest C# 8.0 additions, including asynchronous streams, nullable references, pattern matching, default interface implementation, ranges and new indexing syntax, and changes in the .NET tool chain. Discover how C# supports fundamental coding features, such as classes, other custom types, collections, and error handling Learn how to write high-performance memory-efficient code with .NET Core’s Span and Memory types Query and process diverse data sources, such as in-memory object models, databases, data streams, and XML documents with LINQ Use .NET’s multithreading features to exploit your computer’s parallel processing capabilities Learn how asynchronous language features can help improve application responsiveness and scalability

    It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation.The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.

    The Only Manual You Need to Discover and Use Your Amazon Fire HD 8 & 10 Tablets Like a Pro ***BONUS *** Buy a paperback copy of this book and receive the Kindle version absolutely free via Kindle Matchbook From the Number 1 Best Selling authors in Computers and Technology. This is the Amazon Kindle Fire manual that should have been in the box. Everything you need to know about using your Fire HD 8 & HD 10 tablet explained simply and clearly. No matter what your skill level, this Amazon e-Book will take you from newbie to expert in just 2 hours.User Guide AND Tips, Tricks and Secrets - It's all here.This comprehensive user guide has it all - from simple step by step instructions for the beginner, to expert tips and tricks for the advanced user. This Kindle Fire Amazon e-Book is for everyone. About the AuthorsTom and Jenna Edwards are the Amazon Tech authors behind the Number 1 Bestselling e-book 250+ Best Kindle Fire & Fire HD Apps

    

    

     Create a highly available environment to scale a Docker servers using Kubernetes Implement advance continuous delivery process by parallelizing the pipeline tasks Book Description Continuous Delivery with Docker and Jenkins, Second Edition will explain the advantages of combining Jenkins and Docker to improve the continuous integration and delivery process of an app development. It will start with setting up a Docker server and configuring Jenkins on it. It will then provide steps to build applications on Docker files and integrate them with Jenkins using continuous delivery processes such as continuous integration, automated acceptance testing, and configuration management.Moving on, you will learn how to ensure quick application deployment with Docker containers along with scaling Jenkins using Kubernetes. Next, you will get to know how to deploy applications using Docker images and testing them with Jenkins. Towards the end, the book will touch base with missing parts of the CD pipeline, which are the environments and infrastructure, application versioning, and nonfunctional testing.By the end of the book, you will be enhancing the DevOps workflow by integrating the functionalities of Docker and Jenkins. What you will learn Get to grips with docker fundamentals and how to dockerize an application for the CD process Learn how to use Jenkins on the Cloud environments Scale a pool of Docker servers using Kubernetes Create multi-container applications using Docker Compose Write acceptance tests using Cucumber and run them in the Docker ecosystem using Jenkins Publish a built Docker image to a Docker Registry and deploy cycles of Jenkins pipelines using community best practices Who this book is for The book targets DevOps engineers, system administrators, docker professionals or any stakeholders who would like to explore the power of working with Docker and Jenkins together. No prior knowledge of DevOps is required for this book. Table of Contents Introducing Continuous Delivery Introducing Docker Configuring Jenkins Continuous Integration Pipeline Automated Acceptance Testing Clustering with Kubernetes Configuration Management with Ansible Continuous Delivery Pipeline Advanced Continuous Delivery Appendix: Best Practices

    While there are many OpenShift resources available for developers, this book focuses on the key elements of infrastructure and operations that teams need when looking to integrate and maintain this platform. You'll review important concepts, such as repeatable deployment techniques, advanced OpenShift RBAC capabilities, monitoring clusters, and integrating with external services. You'll also see how to run specialized workloads in OpenShift and how to deploy non-web based applications on the platform, all designed to help cultivate best practices as your organization continue evolve in microservices architectures.OpenShift has become the main enterprise Kubernetes distribution and its market penetration continues to growth at rapid rate. While OpenShift’s documentation provides a great list of configuration options to work with the platform, it can be a daunting task to wade through. Architecting and Operating OpenShift Clusters breaks this content down into clear and useful concepts to provide you with a solid understanding of the OpenShift internal architecture. What You'll Learn Operate high availability in muti-tenant OCP clusters Understand OpenShift SDN models, capabilities, and storage classes Integrate OCP with existing data center capabilities and CI/CD pipelines Support advanced capabilities like: Istio, Multus, Kubernetes Operators, hybrid deployments Who This Book Is For Cloud architects, OpenShift cluster administrators, and teams supporting developers in OpenShift environments who have a basic understanding of this platform and microservices architectures.

    

    By learning Kubernetes, you’ll be able to design your own serverless architecture by implementing the function-as-a-service (FaaS) model.After an accelerated, hands-on overview of the serverless architecture and various Kubernetes concepts, you’ll cover a wide range of real-world development challenges faced by real-world developers, and explore various techniques to overcome them. You’ll learn how to create production-ready Kubernetes clusters and run serverless applications on them. You'll see how Kubernetes platforms and serverless frameworks such as Kubeless, Apache OpenWhisk and OpenFaaS provide the tooling to help you develop serverless applications on Kubernetes. You'll also learn ways to select the appropriate framework for your upcoming project. By the end of this book, you’ll have the skills and confidence to design your own serverless applications using the power and flexibility of Kubernetes. What you will learn Deploy a Kubernetes cluster locally with Minikube Get familiar with AWS Lambda and Google Cloud Functions Create, build, and deploy a webpage generated by the serverless functions in the cloud Create a Kubernetes cluster running on the virtual kubelet hardware abstraction Create, test, troubleshoot, and delete an OpenFaaS function Create a sample Slackbot with Apache OpenWhisk actions Who this book is for This book is for software developers and DevOps engineers who have basic or intermediate knowledge about Kubernetes and want to learn how to create serverless applications that run on Kubernetes. Those who want to design and create serverless applications running on the cloud, or on-premise Kubernetes clusters will also find this book useful. Table of Contents Introduction to Serverless Introduction to Serverless in Cloud Introduction to Serverless Frameworks Kubernetes Deep Dive Production-Ready Kubernetes Clusters Upcoming Serverless Features in Kubernetes Kubernetes Serverless with Kubeless Introduction to Apache OpenWhisk Going Serverless with OpenFaaS

    This book guides you on how to develop these complex systems with the help of containers.You’ll start by learning to design an efficient strategy for migrating a legacy monolithic system to microservices. You’ll build a RESTful microservice with Python and learn how to encapsulate the code for the services into a container using Docker. While developing the services, you’ll understand how to use tools such as GitHub and Travis CI to ensure continuous delivery (CD) and continuous integration (CI). As the systems become complex and grow in size, you’ll be introduced to Kubernetes and explore how to orchestrate a system of containers while managing multiple services. Next, you’ll configure Kubernetes clusters for production-ready environments and secure them for reliable deployments. In the concluding chapters, you’ll learn how to detect and debug critical problems with the help of logs and metrics. Finally, you’ll discover a variety of strategies for working with multiple teams dealing with different microservices for effective collaboration.By the end of this book, you’ll be able to build production-grade microservices as well as orchestrate a complex system of services using containers. What you will learn Discover how to design, test, and operate scalable microservices Coordinate and deploy different services using Kubernetes Use Docker to construct scalable and manageable applications with microservices Understand how to monitor a complete system to ensure early detection of problems Become well versed with migrating from an existing monolithic system to a microservice one Use load balancing to ensure seamless operation between the old monolith and the new service Who this book is for This book is for developers, engineers, or software architects who are trying to move away from traditional approaches for building complex multi-service systems by adopting microservices and containers. Although familiarity with Python programming is assumed, no prior knowledge of Docker is required. Table of Contents Making the Move: Design, Plan, Execute Creating a REST service with Python Build, Run, and Test Your Service Using Docker Creating a pipeline and workflow with GitHub and TravisCI Using Kubernetes Local development with Kubernetes Configuring and Securing the System Using GitOps principles Managing workflows Monitoring Logs and Metrics Handling Change, Dependencies, and Secrets in The System Collaboration and communication between teams

    We will also learn to use transfer learning for multiple applications, including a self-driving car using Convolutional Neural Networks.We will generate images while leveraging GANs and also by performing image encoding. Additionally, we will perform text analysis using word vector based techniques. Later, we will use Recurrent Neural Networks and LSTM to implement chatbot and Machine Translation systems.Finally, you will learn about transcribing images, audio, and generating captions and also use Deep Q-learning to build an agent that plays Space Invaders game.By the end of this book, you will have developed the skills to choose and customize multiple neural network architectures for various deep learning problems you might encounter. What you will learn Build multiple advanced neural network architectures from scratch Explore transfer learning to perform object detection and classification Build self-driving car applications using instance and semantic segmentation Understand data encoding for image, text and recommender systems Implement text analysis using sequence-to-sequence learning Leverage a combination of CNN and RNN to perform end-to-end learning Build agents to play games using deep Q-learning Who this book is for This intermediate-level book targets beginners and intermediate-level machine learning practitioners and data scientists who have just started their journey with neural networks. This book is for those who are looking for resources to help them navigate through the various neural network architectures; you'll build multiple architectures, with concomitant case studies ordered by the complexity of the problem. A basic understanding of Python programming and a familiarity with basic machine learning are all you need to get started with this book. Table of Contents Building a neural network with Tensorflow and Keras Building a Deep Feedforward Neural Network Applications of Deep Feedforward Neural Networks Building a Deep Convolutional Neural Network Transfer Learning Detecting and Localizing Objects in Images Image Analysis Applications in Self-Driving Cars Image Generation Encoding Inputs Text Analysis Using Word Vectors Building a Recurrent Neural Network Applications of a Many-to-One Architecture RNN Sequence-to-Sequence Learning End-to-End Learning Audio Analysis Reinforcement Learning

    

    Abstracting Away the Machine tells the epic story of how they did it--and what happened next.Over the past six decades, programming languages like ALGOL, BASIC, C/C++, COBOL, Java, LISP, LOGO, Pascal, PL/I, Python, Visual Basic, and many others opened up the field of computer science, and of computer programming in general, to the masses. But all of these high-level languages (HLLs)--computer languages that automate, hide, or otherwise abstract away the underlying operations of the machine--owe a huge debt of gratitude to FORTRAN (FORmula TRANslation), the first HLL to achieve widespread adoption. Many programming practices that we take for granted now came about as a result of FORTRAN. Created over a three-year period at IBM by a development team led by a brilliant but wayward mathematician named John W. Backus, FORTRAN was implemented initially on the IBM 704 mainframe computer in the mid-1950s, with dialects of the language quickly spreading thereafter to other platforms. FORTRAN’s powerful compiler, which translated human-readable code into code a computer could understand, produced incredibly clean and optimized standalone executable programs, all of which could be run independently of the compiler, setting the standard for decades to come--and overcoming the doubts of many skeptics along the way, who thought the FORTRAN project would never succeed. In the 1960s the language was standardized, with machine-dependent commands excised, and many platform-independent implementations followed. With the language now portable, able to run on any computer (at least in theory), FORTRAN, almost by accident, secured a stranglehold in the fields of science and engineering. The language also came to dominate in the supercomputing industry.But FORTRAN, a blue-collar workhorse more concerned with results than with style, was a victim of its own success--the language sowed the seeds of its own demise. New high-level languages sprouted up, stealing the good bits from FORTRAN while simultaneously defining themselves in opposition to it. FORTRAN had become the foil. As these new languages pierced the cutting edge of the programming landscape, they redefined computing paradigms (e.g., with structured programming, object-oriented programming, and the like), and FORTRAN--though eventually (and repeatedly) modernized and formally renamed Fortran--struggled to keep up through multiple standardization efforts, finally ceding significant ground to its successors as it slowly withdrew from the spotlight. To add insult to injury, even John Backus eventually turned against his creation.This is not a book on how to program in FORTRAN, nor is it a technical manual. Rather, the focus in Abstracting Away the Machine, which chronicles the complete history and development of the FORTRAN programming language, is set squarely on telling three interlocking stories: (1) How an elite group of computing trailblazers built FORTRAN, (2) Why the conditions at the time were ripe for them to succeed, and (3) What happened after they did. Tracing the long arc of FORTRAN’s development and maturation is integral to understanding not only the history of programming but also the state of computer science today. The birth of FORTRAN planted a seed that led to the full flowering of high-level languages, since FORTRAN overcame initial skepticism by demonstrating to the world that a well-made HLL really could abstract away the machine.

    Αlgorithmic Thinking involves more than just learning code. It is a problem-solving process that involves learning how to code.This edition contains all the popular features of the previous edition and adds a significant number of exercises, as well as extensive revisions and updates. Apart from Python’s lists, it now also covers dictionaries, while a brand new section provides an effective introduction to the next field that a programmer needs to work with, which is Object Oriented Programming (OOP).This book has a class course structure with questions and exercises at the end of each chapter so you can test what you have learned right away and improve your comprehension. With 250 solved and 450 unsolved exercises, 475 true/false, about 150 multiple choice, and 200 review questions and crosswords (the solutions and the answers to which can be found on the Internet), this book is ideal for novices or average programmers, for self-study high school students first-year college or university students teachers professors anyone who wants to start learning or teaching computer programming using the proper conventions and techniques

    It also introduces key concepts such as functions, modules and packages as well as object orientation and functional programming. Each section is prefaced with an introductory chapter, before continuing with how these ideas work in Python.Topics such as generators and coroutines are often misunderstood and these are explained in detail, whilst topics such as Referential Transparency, multiple inheritance and exception handling are presented using examples.A Beginners Guide to Python 3 Programming provides all you need to know about Python, with numerous examples provided throughout including several larger worked case studies illustrating the ideas presented in the previous chapters.

    Covers topics like computer hardware, combinatorial logic, sequential logic, computer architecture, computer anatomy, and Input/Output.Many coders are unfamiliar with the underlying technologies that make their programs run. But why should you care when your code appears to work? Because you want it to run well and not be riddled with hard-to-find bugs. You don't want to be in the news because your code had a security problem.Lots of technical detail is available online but it's not organized or collected into a convenient place. In The Secret Life of Programs, veteran engineer Jonathan E. Steinhart explores--in depth--the foundational concepts that underlie the machine. Subjects like computer hardware, how software behaves on hardware, as well as how people have solved problems using technology over time.You'll learn:  •  How the real world is converted into a form that computers understand, like bits, logic, numbers, text, and colors  •  The fundamental building blocks that make up a computer including logic gates, adders, decoders, registers, and memory  •  Why designing programs to match computer hardware, especially memory, improves performance  •  How programs are converted into machine language that computers understand  •  How software building blocks are combined to create programs like web browsers  •  Clever tricks for making programs more efficient, like loop invariance, strength reduction, and recursive subdivision  •  The fundamentals of computer security and machine intelligence  •  Project design, documentation, scheduling, portability, maintenance, and other practical programming realities.Learn what really happens when your code runs on the machine and you'll learn to craft better, more efficient code.

    It clearly pays dividends to be in the know. This friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. Data Science Programming All-In-One For Dummies is a compilation of the key data science, machine learning, and deep learning programming languages: Python and R. It helps you decide which programming languages are best for specific data science needs. It also gives you the guidelines to build your own projects to solve problems in real time. Get grounded: the ideal start for new data professionals What lies ahead: learn about specific areas that data is transforming   Be meaningful: find out how to tell your data story See clearly: pick up the art of visualization Whether you’re a beginning student or already mid-career, get your copy now and add even more meaning to your life—and everyone else’s!

    

    

     She tries it their way, but when studying and homework don’t result in better grades, Haley makes a desperate deal with a mysterious boy offering an alternative—hacking into the school’s computers to get the answers. As their skills progress, so does their relationship, and soon they are more than just a cyber Bonnie and Clyde. But then Haley gets pregnant and everything starts to unravel. When her foster family discovers she’s pregnant, she ends up on the street and she, Hector, and Jacob have to learn to survive or die trying. As a prequel to the Killchain Chronicles, Script Kiddies sets the foundation for the characters you’ve come to know. If you loved Ransomware, you HAVE to read Script Kiddies.

    With the R Bioinformatics Cookbook, you’ll explore all this and more, tackling common and not-so-common challenges in the bioinformatics domain using real-world examples.This book will use a recipe-based approach to show you how to perform practical research and analysis in computational biology with R. You will learn how to effectively analyze your data with the latest tools in Bioconductor, ggplot, and tidyverse. The book will guide you through the essential tools in Bioconductor to help you understand and carry out protocols in RNAseq, phylogenetics, genomics, and sequence analysis. As you progress, you will get up to speed with how machine learning techniques can be used in the bioinformatics domain. You will gradually develop key computational skills such as creating reusable workflows in R Markdown and packages for code reuse.By the end of this book, you’ll have gained a solid understanding of the most important and widely used techniques in bioinformatic analysis and the tools you need to work with real biological data. What you will learn Employ Bioconductor to determine differential expressions in RNAseq data Run SAMtools and develop pipelines to find single nucleotide polymorphisms (SNPs) and Indels Use ggplot to create and annotate a range of visualizations Query external databases with Ensembl to find functional genomics information Execute large-scale multiple sequence alignment with DECIPHER to perform comparative genomics Use d3.js and Plotly to create dynamic and interactive web graphics Use k-nearest neighbors, support vector machines and random forests to find groups and classify data Who this book is for This book is for bioinformaticians, data analysts, researchers, and R developers who want to address intermediate-to-advanced biological and bioinformatics problems by learning through a recipe-based approach. Working knowledge of R programming language and basic knowledge of bioinformatics are prerequisites. Table of Contents Performing Quantitative RNAseq Finding Genetic Variants With Next-Generation Sequence Data Analyzing Gene and Protein Sequence For Domains and Motifs Phylogenetic Analysis and Visualisation Metagenomics Proteomics from Spectrum to Annotation Producing Publication and Web-Ready Visualizations Working with Databases and Remote Data Sources Useful Statistical and Machine Learning Methods in Bioinformatics Programming and Analysis with Tidyverse Building reusable workflows with packages and objects for code re-use

    With this book, you’ll explore deep learning, and learn how to put machine learning to use in your projects.This second edition of Python Deep Learning will get you up to speed with deep learning, deep neural networks, and how to train them with high-performance algorithms and popular Python frameworks. You’ll uncover different neural network architectures, such as convolutional networks, recurrent neural networks, long short-term memory (LSTM) networks, and capsule networks. You’ll also learn how to solve problems in the fields of computer vision, natural language processing (NLP), and speech recognition. You'll study generative model approaches such as variational autoencoders and Generative Adversarial Networks (GANs) to generate images. As you delve into newly evolved areas of reinforcement learning, you’ll gain an understanding of state-of-the-art algorithms that are the main components behind popular games Go, Atari, and Dota.By the end of the book, you will be well-versed with the theory of deep learning along with its real-world applications. What you will learn Grasp the mathematical theory behind neural networks and deep learning processes Investigate and resolve computer vision challenges using convolutional networks and capsule networks Solve generative tasks using variational autoencoders and Generative Adversarial Networks Implement complex NLP tasks using recurrent networks (LSTM and GRU) and attention models Explore reinforcement learning and understand how agents behave in a complex environment Get up to date with applications of deep learning in autonomous vehicles Who this book is for This book is for data science practitioners, machine learning engineers, and those interested in deep learning who have a basic foundation in machine learning and some Python programming experience. A background in mathematics and conceptual understanding of calculus and statistics will help you gain maximum benefit from this book. Table of Contents Machine Learning – An Introduction Neural Networks Deep Learning Fundamentals Computer Vision With Convolutional Networks Advanced Computer Vision Generating images with GANs and Variational Autoencoders Recurrent Neural Networks and Language Models Reinforcement Learning Theory Deep Reinforcement Learning for Games Deep Learning in Autonomous Vehicles

    

    You will learn how to use Delinkcious, which will serve as a live lab throughout the book to help you understand microservices and Kubernetes concepts in the context of a real-world application. Next, you will get up to speed with setting up a CI/CD pipeline and configuring microservices using Kubernetes ConfigMaps. As you cover later chapters, you will gain hands-on experience in securing microservices, and implementing REST, gRPC APIs, and a Delinkcious data store. In addition to this, you’ll explore the Nuclio project, run a serverless task on Kubernetes, and manage and implement data-intensive tests. Toward the concluding chapters, you’ll deploy microservices on Kubernetes and learn to maintain a well-monitored system. Finally, you’ll discover the importance of service meshes and how to incorporate Istio into the Delinkcious cluster. By the end of this book, you’ll have gained the skills you need to implement microservices on Kubernetes with the help of effective tools and best practices. What you will learn Understand the synergy between Kubernetes and microservices Create a complete CI/CD pipeline for your microservices on Kubernetes Develop microservices on Kubernetes with the Go kit framework using best practices Manage and monitor your system using Kubernetes and open-source tools Expose your services through REST and gRPC APIs Implement and deploy serverless functions as a service Externalize authentication, authorization and traffic shaping using a service mesh Run a Kubernetes cluster in the cloud on Google Kubernetes Engine Who this book is for This book is for developers, DevOps engineers, or anyone who wants to develop large-scale microservice-based systems on top of Kubernetes. If you are looking to use Kubernetes on live production projects or want to migrate existing systems to a modern containerized microservices system, then this book is for you. Coding skills, together with some knowledge of Docker, Kubernetes, and cloud concepts will be useful. Table of Contents Introduction to Kubernetes For Developers Getting Started with Microservices Delinkcious - the sample application Setting Up the CI/CD Pipeline Configuring Microservices using Kubernetes ConfigMaps Securing Microservices on Kubernetes Talking to the World - APIs and Load Balancers Working with Stateful Services Running Serverless Tasks on Kubernetes Testing Microservices Deploying Microservices Monitoring, Logging, and Metrics Service Mesh - Working with Istio

    We will extend pandas offerings with other Python libraries such as matplotlib, NumPy, and scikit-learn to perform each phase and operation of data analysis tasks. You will learn data wrangling, how to manipulate your data, clean it, visualize it, find patterns, and make predictions based on the past data using real-world examples. You will learn how to conduct data analysis, and then take our analyses a step further as we explore some applications of anomaly detection, regression, clustering, and classification.Towards the end of the book, you will be able to use pandas to ensure the veracity of your data, visualize it for effective decision-making, and reliably reproduce analyses across multiple datasets. What you will learn Understand how data analysts and scientists think about gathering and understanding data Perform data analysis and data wrangling in Python  Combine, grouping, and aggregating data from multiple sources Create data visualizations with pandas and matplotlib Learn how to apply machine learning algorithms to make predictions and look for patterns. Use Python Data Science libraries to analyze real-world datasets. Use pandas to solve several common data representation and analysis problems Who This Book Is For This book is for beginners, data analysts, data science professionals, and Python developers who wish to explore every phase of data analysis and scientific computing using wide-range of datasets. If you are a data scientist who is looking to implement pandas offerings in machine learning, you will find this book useful too. You will cover various domains showing the power of pandas. Working knowledge of Python programming language will be beneficial. About the Author Stefanie Molin is a Data Scientist and Software Engineer at Bloomberg LP in NYC (and hacker in training) tackling tough problems in Information Security particularly revolving around anomaly detection, building tools for gathering data, and knowledge sharing. She has extensive experience in data science, designing anomaly detection solutions, and machine learning in both R and Python in the AdTech and FinTech industries. She holds a B.S. in Operations Research from Columbia University’s engineering school with minors in Economics and Entrepreneurship and Innovation.In her free time, she enjoys traveling the world, inventing new recipes, and learning new languages spoken both among people and computers.

    This book contains excellent coverage of the Haskell ecosystem and supporting tools, which include the Cabal build tool for managing projects and modules, the HUnit and QuickCheck tools for software testing, the Scotty framework for developing web applications, Persistent and Esqueleto for database access, and parallel and distributed programming libraries.You'll see how functional programming is gathering momentum, allowing you to express yourself in a more concise way, reducing boilerplate, and increasing the safety of your code. Haskell is an elegant and noise-free pure functional language with a long history, having a huge number of library contributors and an active community. This makes Haskell the best tool for both learning and applying functional programming, and Practical Haskell takes advantage of this to show off the language and what it can do.What You Will LearnGet started programming with HaskellExamine the different parts of the languageGain an overview of the most important libraries and tools in the Haskell ecosystemApply functional patterns in real-world scenariosCarry out data mining Program using MonadsHandle resources with HaskellWho This Book Is ForExperienced programmers who may be new to the Haskell programming language. However, some prior exposure to Haskell is recommended.

    Author Perry Carpenter delivers a wealth of practical insight that transcends traditional security education by incorporating best practices from experts in communication, persuasion, innovation, behavioral science, and storytelling to give readers tools that will make a lasting impact in their organizations. In Solving the Security Awareness Puzzle Perry will cover: Marketing, Behavior Science, and Culture Management for Security Awareness Program ManagersHow to effectively use simulations, games, surveys, and new trends like escape rooms to teach security awarenessPutting the effective training together into a well-crafted campaign with ambassadorsMeasuring your success and establishing continuous improvements

    The R language provides everything you need to do statistical work, but its structure can be difficult to master. These task-oriented recipes make you productive with R immediately. Solutions range from basic tasks to input and output, general statistics, graphics, and linear regression.Each recipe addresses a specific problem and includes a discussion that explains the solution and provides insight into how it works. If you're a beginner, R Cookbook will help get you started. If you're an intermediate user, this book will jog your memory and expand your horizons. You'll get the job done faster and learn more about R in the process.Create vectors, handle variables, and perform basic functionsSimplify data input and outputTackle data structures such as matrices, lists, factors, and data framesWork with probability, probability distributions, and random variablesCalculate statistics and confidence intervals and perform statistical testsCreate a variety of graphic displaysBuild statistical models with linear regressions and analysis of variance (ANOVA)Explore advanced statistical techniques, such as finding clusters in your data