Until now. This practical guide provides the first comprehensive overview of software architecture's many aspects. You'll examine architectural characteristics, architectural patterns, component determination, diagramming and presenting architecture, evolutionary architecture, and many other topics.Authors Neal Ford and Mark Richards help you learn through examples in a variety of popular programming languages, such as Java, C#, JavaScript, and others. You'll focus on architecture principles with examples that apply across all technology stacks.

    This book provides a step-by-step framework on how to tackle a system design question. It includes many real-world examples to illustrate the systematic approach with detailed steps that you can follow.What’s inside?- An insider’s take on what interviewers really look for and why.- A 4-step framework for solving any system design interview question.- 15 real system design interview questions with detailed solutions.- 188 diagrams to visually explain how different systems work.Table Of ContentsChapter 1: Scale From Zero To Millions Of UsersChapter 2: Back-of-the-envelope EstimationChapter 3: A Framework For System Design InterviewsChapter 4: Design A Rate LimiterChapter 5: Design Consistent HashingChapter 6: Design A Key-value StoreChapter 7: Design A Unique Id Generator In Distributed SystemsChapter 8: Design A Url ShortenerChapter 9: Design A Web CrawlerChapter 10: Design A Notification SystemChapter 11: Design A News Feed SystemChapter 12: Design A Chat SystemChapter 13: Design A Search Autocomplete SystemChapter 14: Design YoutubeChapter 15: Design Google DriveChapter 16: The Learning Continues

    In addition to making technical decisions, architects can help change the organization's structure and processes to support this transition. To do that, architects need to take the express elevator from the engine room to the penthouse, where business strategy resides.Brimming with anecdotes from actual IT transformations, this book prepares software architects, senior developers, and other IT professionals for a more complex but rewarding role in the enterprise.This book is ideal for:Architects and senior developers looking to shape the company's technology direction or assist in an organizational transformationEnterprise architects and senior technologists looking for practical advice on how to navigate technical and organizational topicsCTOs and senior technical architects who want to learn what's worked and what hasn't in large-scale architecture and transformationIT managers seeking to understand how architecture can support their technical transformation agenda

    This practical guide by experimentation leaders at Google, LinkedIn, and Microsoft will teach you how to accelerate innovation using trustworthy online controlled experiments, or A/B tests. Based on practical experiences at companies that each run more than 20,000 controlled experiments a year, the authors share examples, pitfalls, and advice for students and industry professionals getting started with experiments, plus deeper dives into advanced topics for practitioners who want to improve the way they make data-driven decisions. Learn how to - Use the scientific method to evaluate hypotheses using controlled experiments - Define key metrics and ideally an Overall Evaluation Criterion - Test for trustworthiness of the results and alert experimenters to violated assumptions - Build a scalable platform that lowers the marginal cost of experiments close to zero - Avoid pitfalls like carryover effects and Twyman's law - Understand how statistical issues play out in practice.

    Many Python developers are now taking an interest in high-level software architecture patterns such as hexagonal/clean architecture, event-driven architecture, and strategic patterns prescribed by domain-driven design (DDD). But translating those patterns into Python isn't always straightforward.With this practical guide, Harry Percival and Bob Gregory from MADE.com introduce proven architectural design patterns to help Python developers manage application complexity. Each pattern is illustrated with concrete examples in idiomatic Python that explain how to avoid some of the unnecessary verbosity of Java and C# syntax. You'll learn how to implement each of these patterns in a Pythonic way.Architectural design patterns include:Dependency inversion, and its links to ports and adapters (hexagonal/clean architecture)Domain-driven design's distinction between entities, value objects, and aggregatesRepository and Unit of Work patterns for persistent storageEvents, commands, and the message busCommand Query Responsibility Segregation (CQRS)Event-driven architecture and reactive microservices

    

    But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications.Authors Jeremy Howard and Sylvain Gugger show you how to train a model on a wide range of tasks using fastai and PyTorch. You'll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes.Train models in computer vision, natural language processing, tabular data, and collaborative filteringLearn the latest deep learning techniques that matter most in practiceImprove accuracy, speed, and reliability by understanding how deep learning models workDiscover how to turn your models into web applicationsImplement deep learning algorithms from scratchConsider the ethical implications of your work

    With this book, you'll get a candid and insightful look at how software is constructed and maintained by some of the world's leading practitioners.Titus Winters, Tom Manshreck, and Hyrum K. Wright, software engineers and a technical writer at Google, reframe how software engineering is practiced and taught: from an emphasis on programming to an emphasis on software engineering, which roughly translates to programming over time.You'll learn:Fundamental differences between software engineering and programmingHow an organization effectively manages a living codebase and efficiently responds to inevitable changeWhy culture (and recognizing it) is important, and how processes, practices, and tools come into play

    But how do you know if the deployment is secure? This practical book examines key underlying technologies to help developers, operators, and security professionals assess security risks and determine appropriate solutions.Author Liz Rice, Chief Open Source Officer at Isovalent, looks at how the building blocks commonly used in container-based systems are constructed in Linux. You'll understand what's happening when you deploy containers and learn how to assess potential security risks that could affect your deployments. If you run container applications with kubectl or docker and use Linux command-line tools such as ps and grep, you're ready to get started.Explore attack vectors that affect container deploymentsDive into the Linux constructs that underpin containersExamine measures for hardening containersUnderstand how misconfigurations can compromise container isolationLearn best practices for building container imagesIdentify container images that have known software vulnerabilitiesLeverage secure connections between containersUse security tooling to prevent attacks on your deployment

    By adopting the micro frontends approach and designing your web apps as systems of features, you can deliver faster feature development, easier upgrades, and pick and choose the technology you use in your stack. Micro Frontends in Action is your guide to simplifying unwieldy frontends by composing them from small, well-defined units. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Micro frontends deliver the same flexibility and maintainability to browser-based applications that microservices provide for backend systems. You design your project as a set of standalone components that include their own interfaces, logic, and storage. Then you develop these mini-applications independently and compose them in the browser. About the Book Micro Frontends in Action teaches you to apply the microservices approach to the frontend. You’ll start with the core micro frontend design ideas. Then, you’ll build an e-commerce application, working through practical issues like server-side and client-side composition, routing, and maintaining a consistent look and feel. Finally, you’ll explore team workflow patterns that maximize the benefit of developing application components independently. What’s Inside -    Create a unified frontend from independent applications -    Combine JavaScript code from multiple frameworks -    Browser and server-side composition and routing -    Implement effective dev teams and project workflow About the Reader For web developers, software architects, and team leaders. About the Author Michael Geers is a software developer specializing in building user interfaces. Table of Contents PART 1 - GETTING STARTED WITH MICRO FRONTENDS 1 What are micro frontends? 2 My first micro frontends project PART 2 - ROUTING, COMPOSITION, AND COMMUNICATION 3 Composition with Ajax and server-side routing 4 Server-side composition 5 Client-side composition 6 Communication patterns 7 Client-side routing and the application shell 8 Composition and universal rendering 9 Which architecture fits my project? PART 3 - HOW TO BE FAST, CONSISTENT, AND EFFECTIVE 10 Asset loading 11 Performance is key 12 User interface and design system 13 Teams and boundaries 14 Migration, local development, and testing

    But with a million blogs, books, and videos out there, just where do you start? The worldwide best selling "You Don't Know JS" book series is back for a 2nd edition: "You Don't Know JS Yet". All 6 books are brand new, rewritten to cover all sides of JS for 2020 and beyond. "Get Started" prepares you for the journey ahead, first surveying the language then detailing how the rest of the You Don't Know JS Yet book series guides you to knowing JS more deeply.

    Learn how to manage this complexity and make sure you keep providing a quality GraphQL API as your team or organization scales.Every language and every GraphQL implementation does things slightly differently. This book is completely language agnostic and instead focuses on concepts and patterns that are achievable no matter how you're building a GraphQL server.Think of it as a complete journey of what goes into building a GraphQL API, from design, to architectures, to implementation, and even documentation.

    Cloud computing is an amazing resource that can provide fully managed platforms, auto-optimizing and even auto-healing operations, per-second billing, pre-trained machine learning models, and globally distributed transactional data stores. So, it’s no wonder that most enterprises want to take advantage of such capabilities.Still, migrating a whole enterprise to the cloud isn’t easy. Migration itself can be a costly endeavor while simply lifting and shifting legacy applications to the cloud is unlikely to bring the anticipated benefits. At the same time, re-architecting applications to run optimally in the cloud is likely to be cost prohibitive. So, enterprises need to have a better and more nuanced strategy than just “Cloud First!”Harvested from half a decade of moving organizations to the cloud, this book presents a fresh take on cloud computing. Staying clear of product pitches and buzzwords, it takes a deeper look at both the architectural choices but also the organizational implications of adopting cloud. It helps IT leaders devise a cohesive strategy that utilizes an organization’s existing assets while also fundamentally transforming the way it looks at IT.

    This is a comprehensive guide about the principles, strategies and tactics developers can use to build an awesome career!Career Guides.Specific advice on every career stage from Code Newbie to Junior Dev to Senior Dev, and every transition after: the First Job Hunt, going from Junior to Senior, and Beyond.Principles.The best investments are in things that don't change. We discuss timeless rules for successful default behaviour. Learn to grow your network and expertise, while you learn.Strategies.Everything to do with making big moves, from Betting on Technologies, to Career Ladders, to Software Business Models. Grow your business and personal impact!TacticsImportant, self-contained skills that you can repeatedly call on throughout your career, from Negotiating to Side Projects to Twitter to Writing.

    Switching from thin tailed to fat tailed distributions requires more than "changing the color of the dress." Traditional asymptotics deal mainly with either n=1 or n=∞, and the real world is in between, under the "laws of the medium numbers"-which vary widely across specific distributions. Both the law of large numbers and the generalized central limit mechanisms operate in highly idiosyncratic ways outside the standard Gaussian or Levy-Stable basins of convergence. A few examples: - The sample mean is rarely in line with the population mean, with effect on "na�ve empiricism," but can be sometimes be estimated via parametric methods. - The "empirical distribution" is rarely empirical. - Parameter uncertainty has compounding effects on statistical metrics. - Dimension reduction (principal components) fails. - Inequality estimators (Gini or quantile contributions) are not additive and produce wrong results. - Many "biases" found in psychology become entirely rational under more sophisticated probability distributions. - Most of the failures of financial economics, econometrics, and behavioral economics can be attributed to using the wrong distributions. This book, the first volume of the Technical Incerto, weaves a narrative around published journal articles.

    In it, you’ll learn practical Docker skills to help you tackle the challenges of modern IT, from cloud migration and microservices to handling legacy systems. There’s no excessive theory or niche-use cases—just a quick-and-easy guide to the essentials of Docker you’ll use every day. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology The idea behind Docker is simple: package applica­tions in lightweight virtual containers that can be easily installed. The results of this simple idea are huge! Docker makes it possible to manage applications without creating custom infrastructures. Free, open source, and battle-tested, Docker has quickly become must-know technology for developers and administrators. About the book Learn Docker in a Month of Lunches introduces Docker concepts through a series of brief hands-on lessons. Follow­ing a learning path perfected by author Elton Stoneman, you’ll run containers by chapter 2 and package applications by chapter 3. Each lesson teaches a practical skill you can practice on Windows, macOS, and Linux systems. By the end of the month you’ll know how to containerize and run any kind of application with Docker. What's inside     Package applications to run in containers     Put containers into production     Build optimized Docker images     Run containerized apps at scale About the reader For IT professionals. No previous Docker experience required. About the author Elton Stoneman is a consultant, a former architect at Docker, a Microsoft MVP, and a Pluralsight author. Table of Contents PART 1 - UNDERSTANDING DOCKER CONTAINERS AND IMAGES 1. Before you begin 2. Understanding Docker and running Hello World 3. Building your own Docker images 4. Packaging applications from source code into Docker Images 5. Sharing images with Docker Hub and other registries 6. Using Docker volumes for persistent storage PART 2 - RUNNING DISTRIBUTED APPLICATIONS IN CONTAINERS 7. Running multi-container apps with Docker Compose 8. Supporting reliability with health checks and dependency checks 9. Adding observability with containerized monitoring 10. Running multiple environments with Docker Compose 11. Building and testing applications with Docker and Docker Compose PART 3 - RUNNING AT SCALE WITH A CONTAINER ORCHESTRATOR 12. Understanding orchestration: Docker Swarm and Kubernetes 13. Deploying distributed applications as stacks in Docker Swarm 14. Automating releases with upgrades and rollbacks 15. Configuring Docker for secure remote access and CI/CD 16. Building Docker images that run anywhere: Linux, Windows, Intel, and Arm PART 4 - GETTING YOUR CONTAINERS READY FOR PRODUCTION 17. Optimizing your Docker images for size, speed, and security 18. Application configuration management in containers 19. Writing and managing application logs with Docker 20. Controlling HTTP traffic to containers with a reverse proxy 21. Asynchronous communication with a message queue 22. Never the end

    This book covers all the basic subjects such as threat modeling and security testing, but also dives deep into more complex and advanced topics for securing modern software systems and architectures. Throughout, the book offers analogies, stories of the characters Alice and Bob, real-life examples, technical explanations and diagrams to ensure maximum clarity of the many abstract and complicated subjects. Topics include:Secure requirements, design, coding, and deployment Security Testing (all forms) Common Pitfalls Application Security Programs Securing Modern Applications Software Developer Security Hygiene Alice and Bob Learn Application Security is perfect for aspiring application security engineers and practicing software developers, as well as software project managers, penetration testers, and chief information security officers who seek to build or improve their application security programs.Alice and Bob Learn Application Security illustrates all the included concepts with easy-to-understand examples and concrete practical applications, furthering the reader's ability to grasp and retain the foundational and advanced topics contained within.

    In addition to covering more advanced materials relevant to its companion, The x-Chapters also includes extensive treatment of many topics in electronics that are particularly novel, important, or just exotic and intriguing. Think of The x-Chapters as the missing pieces of The Art of Electronics, to be used either as its complement, or as a direct route to exploring some of the most exciting and oft-overlooked topics in advanced electronic engineering. This enticing spread of electronics wisdom and expertise will be an invaluable addition to the library of any student, researcher, or practitioner with even a passing interest in the design and analysis of electronic circuits and instruments. You'll find here techniques and circuits that are available nowhere else.

    PyTorch puts these superpowers in your hands, providing a comfortable Python experience that gets you started quickly and then grows with you as you—and your deep learning skills—become more sophisticated. Deep Learning with PyTorch will make that journey engaging and fun.

    Building a Career in Software is the solution, a comprehensive guide to the essential skills that instructors don't need and professionals never think to teach: landing jobs, choosing teams and projects, asking good questions, running meetings, going on-call, debugging production problems, technical writing, making the most of a mentor, and much more.In over a decade building software at companies such as Apple and Uber, Daniel Heller has mentored and managed tens of engineers from a variety of training backgrounds, and those engineers inspired this book with their hundreds of questions about career issues and day-to-day problems. Designed for either random access or cover-to-cover reading, it offers concise treatments of virtually every non-technical challenge you will face in the first five years of your career--as well as a selection of industry-focused technical topics rarely covered in training. Whatever your education or technical specialty, Building a Career in Software can save you years of trial and error and help you succeed as a real-world software professional.What You Will LearnDiscover every important nontechnical facet of professional programming as well as several key technical practices essential to the transition from student to professionalBuild relationships with your employerImprove your communication, including technical writing, asking good questions, and public speakingWho This Book is ForSoftware engineers either early in their careers or about to transition to the professional world; that is, all graduates of computer science or software engineering university programs and all software engineering boot camp participants.

    Through the course of this hands-on book, you'll build an example ML-driven application from initial idea to deployed product. Data scientists, software engineers, and product managers with little or no ML experience will learn the tools, best practices, and challenges involved in building a real-world ML application step-by-step.Author Emmanuel Ameisen, who worked as a data scientist at Zipcar and led Insight Data Science's AI program, demonstrates key ML concepts with code snippets, illustrations, and screenshots from the book's example application.The first part of this guide shows you how to plan and measure success for an ML application. Part II shows you how to build a working ML model, and Part III explains how to improve the model until it fulfills your original vision. Part IV covers deployment and monitoring strategies.This book will help you:Determine your product goal and set up a machine learning problemBuild your first end-to-end pipeline quickly and acquire an initial datasetTrain and evaluate your ML model and address performance bottlenecksDeploy and monitor models in a production environment

    

    

    This means that some students hardly talk at all. Yet, talking and writing about in-process and unfinished ideas are vital to learning mathematics. How can we meet this challenge? Amanda (Mandy) Jansen and her collaborating teachers have developed a breakthrough approach: expand the idea of 'rough drafts' to the mathematics classroom. In Rough Draft Math, Mandy shares the power of infusing math class with the spirit of revision so that students feel comfortable thinking aloud as they talk to learn through problem-solving rather than talking only to perform right answers. In the process, a class of students becomes a community of mathematical thinkers, and teachers gain access into their students’ ideas and understandings. Inside you’ll find the following:an exploration of what the idea of revision could mean for math teaching and learningclassroom vignettes to see rough draft math in actionspecific teaching techniques to encourage and practice rough draft thinkingvoices of teachers and students in rough draft classroomsMandy’s reflections about her own teaching as a work in progressIn Rough Draft Math, Mandy shows how to create a classroom culture in which your students will feel more comfortable expressing their partial understandings and in-process thinking, and then continually revising that thinking as they build deep, conceptual understanding of mathematics.

    Unlike the previous version of the exam, the official Exam objectives released for this exam are too vague. Some candidates have reported getting questions on topics that are too advanced or are not mentioned in the objectives. Your feedback on such topics will help improve the content. 2. This book DOES NOT include mock exams. It is meant to complement Enthuware Mock Exams and should be used as a study guide before or while attempting the mock Exams. OCP Oracle Certified Professional Java SE 11 Programmer Part 1 Exam Fundamentals is a comprehensive study guide for those taking the Oracle Certified Professional Java SE 11 Programmer I Exam (Exam Code 1Z0-815). With complete coverage of 100% of the exam objectives, this book provides everything you need to know to take the exam confidently. Written by an expert with more than 20 years of industry experience, the book also helps you ace technical interviews by making you aware of things that technical managers focus on. The Java 11 exam requires you to learn new features of the language including modules, generics, and functional programming. This book covers all such topics thoroughly. The book also includes coding exercises that will get you moving on "write a lot of code" front. The book makes it easy to get your doubts cleared by including links to existing discussion on a particular topic. If the existing discussion doesn't address your doubt, you can see more clarification from the Author.

    But how can you process such varied workloads efficiently? Enter Apache Spark.Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you'll be able to:Learn Python, SQL, Scala, or Java high-level Structured APIsUnderstand Spark operations and SQL EngineInspect, tune, and debug Spark operations with Spark configurations and Spark UIConnect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or KafkaPerform analytics on batch and streaming data using Structured StreamingBuild reliable data pipelines with open source Delta Lake and SparkDevelop machine learning pipelines with MLlib and productionize models using MLflow

    Readers learn how to use key deep learning algorithms without the need for complex math.Deep Learning algorithms can start with mountains of data and measurements and turn them into useful and meaningful patterns. This book is for people with sharp minds who may lack the math background necessary to deal with equations or complex mechanics, but who nevertheless want to understand the "how" of deep learning, and actually use these tools for themselves.Deep Learning: A Visual Approach helps demystify the algorithms that enable computers to drive cars, win chess tournaments, and create symphonies, while giving readers the tools necessary to build their own systems to help them find the information hiding within their own data, create "deep dream" artwork, or create new stories in the style of their favorite authors. Scientists, artists, programmers, managers, hobbyists, and intellectual adventurers of all kinds can use deep learning tools to make new discoveries and create new kinds of art and intelligent systems.The book's friendly, informal approach to deep learning demonstrates the concepts visually. There's no math beyond the occasional multiplication and no programming experience is required. By the end of the book, readers will be equipped to understand modern deep learning systems, and anyone who wants to program and train their own deep learning networks will be able to dive into the library of their choice and start implementing with knowledge and confidence.

    

    Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher-quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

    

    The fields of application of the language range from machine learning, over computer networking to business applications.In this 7 in 1 version you get a full collection of The Python Bible series. From the first volume on, you will be lead on a structured way to the mastery of Python. Besides the basics and the intermediate concepts, you will also learn how to apply it in areas like machine learning, financial analysis and neural networks. At the end you will additionally be introduced to one of the most interesting fields of computer science, which is computer vision After reading this collection, you will not only understand the programming language but you will also be able to work on projects in the stated fields. You will become a true Python expert!What You Will Learn:Beginner Level:• Basics of Programming with Python• Automation of Simple Processes• Programming of Modular Python Applications• Easy Transition to Other Languages (Java, C++ etc.)Intermediate Level:• Object-Oriented Programming• Network Programming• Penetration Testing with Python• Regular Expressions• Multithreading• XML Processing• Database Programming• LoggingData Science:• Analyzing and Processing Big Data• Statistical Calculations with Python• Visualization of Data• Working with NumPy, Matplotlib and PandasMachine Learning:• Predicting Data with Machine Learning• Building Neural Networks with Tensorflow• Recognizing Handwritten Digits with Neural Networks• Applying Linear Models like Regression• K-Nearest-Neighbors Classification• K-Means Clustering• Support Vector MachinesFinance:• Financial Analysis with Python• Analyzing and Graphing Stock Data• Plotting Trendlines• Predicting Share Prices with Machine LearningNeural Networks:• Generating Poetic Texts with Neural Networks• Predicting Sequential Data (Stocks, Weather etc.)• Processing Audio and Video Data• Recognizing Objects Like Horses, Cars and Trucks on Images• Understanding Recurrent Neural Networks• Understanding Convolutional Neural NetworksComputer Vision:• Making unreadable texts readable again with thresholding• Extracting essential information out of images and videos• Edge detection• Template matching and feature matching• Movement detection in videos• Professional object recognition with OpenCVStart Your Journey And Become A Python Expert With The Python Bible!

    Dozens of experts and influential security specialists reveal their best strategies for building, leading, and managing information security within organizations. Tribe of Hackers Security Leaders follows the same bestselling format as the original Tribe of Hackers, but with a detailed focus on how information security leaders impact organizational security.Information security is becoming more important and more valuable all the time. Security breaches can be costly, even shutting businessesand governments down, so security leadership is a high-stakes game. Leading teams of hackers is not always easy, but the future of your organization may depend on it. In this book, the world's top security experts answer the questions that Chief Information Security Officers and other security leaders are asking, including:What's the most important decision you've made or action you've taken to enable a business risk? How do you lead your team to execute and get results? Do you have a workforce philosophy or unique approach to talent acquisition? Have you created a cohesive strategy for your information security program or business unit? Anyone in or aspiring to an information security leadership role, whether at a team level or organization-wide, needs to read this book. Tribe of Hackers Security Leaders has the real-world advice and practical guidance you need to advance your cybersecurity leadership career.

    After you master them, the usual career transition is into more architecture roles, such as choosing the best possible approaches for solving particular test automation challenges. You will get an access to more than 20000+ lines of real-world code examples.Who This Book Is ForThe book is NOT a getting started guide! If you don't have any prior programming experience in writing automated tests through WebDriver, I suggest you to first start with some book about basic programming and basic WebDriver usage. I believe it might be invaluable for the readers that have a couple of years of experience and whose job is to create/maintain test automation frameworks, or to write high-quality reliable automated tests.The book is written in C#. However, I think that you can use the approaches and practices in every OOP language. If you have a Java background (or similar), you will get everything you need, don't worry.Even if you don't get all the concepts from the first read, try to use and incorporate some of them, later you can return and reread them. I believe with the accumulation of experience using high-quality practices- you will become a hard-core test automation ninja!What You Will Learn Learn how to optimize and stabilize your flaky tests. Learn how to handle asnynchronious web pages in your tests. Automatically deal with AJAX and jQuery.Improve Test Readability, Maintainability, Reusability, Extensibility by incorporating 10+ design patterns: Page Object Model, Facade, Decorator, Observer, Strategy, Singleton, Fluent Interface, Template Method, Abstract Factory, Factory Method, Repository, Lazy Load. Learn what are the SOLID principles and how they can improve your test code. We will also discuss other essential programming principles such as composition, DRY, KISS and others. Learn how to asses and choose the best possible design for your framework or library. Learn how the benchmarking your code can help you to speed up your tests. Learn how to design and build your framework to handle test data and different test environments. Learn about high quality code practices and naming convention so that your code get much more understandable.

    Written especially for object-oriented programmers, it will help you map familiar ideas like objects and inheritance to FP concepts such as programming with immutable data, higher order functions, composing functions, concurrent programming and even the dreaded monad. And you'll be pleased to know that we skip the academic baggage of lambda calculus, category theory, and the mathematical foundations of FP in favor of applying functional programming to everyday programming tasks. At the end of the book, you'll be ready to pick a functional language and start writing useful software.

    With PowerShell, you can automate tasks with scripts without having to learn the complicated ins and outs of programming. After you familiarize yourself with PowerShell's intuitive syntax, you'll apply your knowledge by designing and developing scripts for lots of daily situations IT personnel find themselves in every day. You'll then end with learning how to build a large project to automate server deployments from scratch written completely in PowerShell.In Part One, you'll be brought up to an intermediate knowledge level of PowerShell by exploring the ins and outs of core concepts with PowerShell's intuitive syntax.In Part Two, you'll begin to apply your knowledge and develop various scripts to automate all kinds of real-world tasks that a tech professional may run into.Finally, in Part Three, you will take all of that knowledge you learned in the first two parts and begin work on a large PowerShell module called PowerLab. In this Part, you will build a real-world project purely in PowerShell that will teach you that PowerShell isn't just for a few scripts here and there! This PowerLab module will enable you to automatically create Hyper-V virtual machines, install Windows servers, and provision domain controllers, IIS web servers, and SQL servers.With this book's vast amount of real-world, applicable examples coming from an author who's lived PowerShell for over 8 years, you'll uncover hundreds of tactics and techniques that even the most seasoned PowerShell expert may not know. Unlock the possibilities with PowerShell!

    Authors Valliappa Lakshmanan, Sara Robinson, and Michael Munn catalog the first tried-and-proven methods to help engineers tackle problems that frequently crop up during the ML process. These design patterns codify the experience of hundreds of experts into advice you can easily follow.The authors, three Google Cloud engineers, describe 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the most appropriate remedy for your situation.You’ll learn how to:Identify and mitigate common challenges when training, evaluating, and deploying ML modelsRepresent data for different ML model types, including embeddings, feature crosses, and moreChoose the right model type for specific problemsBuild a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuningDeploy scalable ML systems that you can retrain and update to reflect new dataInterpret model predictions for stakeholders and ensure that models are treating users fairly

    This book combines annotated Python code with intuitive explanations to explore DRL techniques. You’ll see how algorithms function and learn to develop your own DRL agents using evaluative feedback.Summary We all learn through trial and error. We avoid the things that cause us to experience pain and failure. We embrace and build on the things that give us reward and success. This common pattern is the foundation of deep reinforcement learning: building machine learning systems that explore and learn based on the responses of the environment. Grokking Deep Reinforcement Learning introduces this powerful machine learning approach, using examples, illustrations, exercises, and crystal-clear teaching. You'll love the perfectly paced teaching and the clever, engaging writing style as you dig into this awesome exploration of reinforcement learning fundamentals, effective deep learning techniques, and practical applications in this emerging field. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology We learn by interacting with our environment, and the rewards or punishments we experience guide our future behavior. Deep reinforcement learning brings that same natural process to artificial intelligence, analyzing results to uncover the most efficient ways forward. DRL agents can improve marketing campaigns, predict stock performance, and beat grand masters in Go and chess. About the book Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems. This book combines annotated Python code with intuitive explanations to explore DRL techniques. You’ll see how algorithms function and learn to develop your own DRL agents using evaluative feedback. What's inside     An introduction to reinforcement learning     DRL agents with human-like behaviors     Applying DRL to complex situations About the reader For developers with basic deep learning experience. About the author Miguel Morales works on reinforcement learning at Lockheed Martin and is an instructor for the Georgia Institute of Technology’s Reinforcement Learning and Decision Making course. Table of Contents 1 Introduction to deep reinforcement learning 2 Mathematical foundations of reinforcement learning 3 Balancing immediate and long-term goals 4 Balancing the gathering and use of information 5 Evaluating agents’ behaviors 6 Improving agents’ behaviors 7 Achieving goals more effectively and efficiently 8 Introduction to value-based deep reinforcement learning 9 More stable value-based methods 10 Sample-efficient value-based methods 11 Policy-gradient and actor-critic methods 12 Advanced actor-critic methods 13 Toward artificial general intelligence

    To name just a few areas: High-PerformanceComputing (HPC), Game Development, data-center applications (like Facebook, Google, etc.),High-Frequency Trading. But the scope of the book is not limited to the mentioned industries.This book will be useful for any developer who wants to understand the performance of theirapplication better and know how it can be diagnosed and improved. The author hopes that3the material presented in this book will help readers develop new skills that can be applied intheir daily work."

    Well, let me surprise you! Linux is simple and easy to learn, and this book is the ultimate proof!You may have stumbled across a variety of sources that all explain Linux in a complicated and dry manner. This book does exactly the opposite; it teaches you Linux in a delightful and friendly way so that you will never get bored, and you will always feel motivated to learn more.Learn Linux Quickly doesn't assume any prior Linux knowledge, which makes it a perfect fit for beginners. Nevertheless, intermediate and advanced Linux users will still find this book very useful as it goes through a wide range of topics. Learn Linux Quickly will teach you the following topics:Installing LinuxOver 116 Linux CommandsUser and Group ManagementLinux Networking FundamentalsBash ScriptingAutomate Boring Tasks with Cron JobsCreate your Own Linux CommandsLinux Disk Partitioning and LVMFinding Files on LinuxUnderstanding File PermissionsLinux ProcessesAnd much more! There is no time to waste here! Learn Linux Quickly and kick start your Linux career today!

    

    So in this short book, we will help you build a mental model of how SwiftUI works. We explain the most important concepts in detail, and we follow them up with exercises to give you hands-on experience.SwiftUI is still a young framework, and as such, we don’t believe it’s appropriate to write a complete reference. Instead, this book focuses on transitioning your way of thinking from the object-oriented style of UIKit to the declarative style of SwiftUI.Thinking in SwiftUI is geared toward readers who are familiar with Swift and who have experience building apps in frameworks like UIKit.

    In this book, Peter, Uwe, and Kurt have provided a collection of materials to help the Scrum Team deliver value and feel happy doing it." --Dave West, CEO and Product Owner, Scrum.org Teams and individuals find the rules of the Scrum Framework to be easy to describe but challenging to implement. The Professional Scrum Team helps you bring the Scrum Framework rules to life in your everyday work, optimizing both team and individual performance and creating more value.Three leading Scrum experts bring together proven practices based on decades of real-life experience participating in, leading, and supporting Scrum Teams. They introduce a team as it starts out with Scrum and follow it as it gains hard-won practical experience, gradually mastering the intense collaboration that Scrum demands.As you share the team's experience--facing and overcoming realistic challenges--you'll discover better ways to work together, enhance your practices, leverage tools, continuously improve, and deliver functionality in ever-shorter cycles. Understand how Scrum Teams work, collaborate, and promote transparency Explore common problems that lead less experienced Scrum Teams to give up Find your Scrum Team's best approach to solving complex adaptive problems Integrate DevOps practices with Scrum to improve effectiveness Productively and professionally resolve conflicts that arise from close collaboration Help your organization learn how to improve its results by better supporting its Scrum Teams This guide is for anyone who works with Scrum Teams or wants to become more effective as a Scrum Team member or leader.Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

    Learn to study better and get better grades using mnemonic devices, definitions, diagrams, educational doodles, and quizzes to recap it all. Including: Atoms, elements, compounds and mixturesThe periodic tableQuantum theoryBondingThe moleChemical reactions and calculations Gas laws Solubility pH scaleTitrations Le Chatelier's principle...and much more!

    The reason? Bad data semantics.In this practical and comprehensive field guide, author Panos Alexopoulos takes you on an eye-opening journey through semantic data modeling as applied in the real world. You'll learn how to master this craft to increase the usability and value of your data and applications. You'll also explore the pitfalls to avoid and dilemmas to overcome for building high-quality and valuable semantic representations of data.Understand the fundamental concepts, phenomena, and processes related to semantic data modelingExamine the quirks and challenges of semantic data modeling and learn how to effectively leverage the available frameworks and toolsAvoid mistakes and bad practices that can undermine your efforts to create good data modelsLearn about model development dilemmas, including representation, expressiveness and content, development, and governanceOrganize and execute semantic data initiatives in your organization, tackling technical, strategic, and organizational challenges

    With this hands-on guide, Java engineers will learn how to use their language experience in the new world of serverless computing. You'll discover how this cloud computing model can drastically reduce the complexity in developing and operating applications while reducing costs and time to market.Engineering leaders John Chapin and Mike Roberts guide you through the process of developing serverless applications using AWS Lambda, Amazon's event-driven, serverless computing platform. You'll learn how to prepare the development environment, program Lambda functions, and deploy and operate your serverless software. Chapters includes exercises to help you through each aspect of the process.Get an introduction to serverless, functions-as-a-service, and AWS LambdaLearn how to deploy working Lambda functions to the cloudProgram Lambda functions and learn how to get data in and outBuild and package Java-based Lambda code and dependenciesCreate serverless applications by building a serverless API and data pipelineTest your serverless applications using automated techniquesApply advanced techniques to build production-ready applications

    Although top executives do not make the day-to-day technical decisions related to cybersecurity, they can direct the company from the top down to have a security mindset. As this book explains, executives can build systems and processes that track gaps and security problems while still allowing for innovation and achievement of business objectives. Many of the data breaches occurring today are the result of fundamental security problems, not crafty attacks by insidious malware. The way many companies are moving to cloud environments exacerbates these problems. However, cloud platforms can also help organizations reduce risk if organizations understand how to leverage their benefits. If and when a breach does happen, a company that has the appropriate metrics can more quickly pinpoint and correct the root cause. Over time, as organizations mature, they can fend off and identify advanced threats more effectively. RECOMMENDATION: As a former senior military leader I learned early on that my personal expertise of a subject was less important than my ability to ask better questions of the experts. Often I had no expertise at all but was required to make critical high risk decisions under very tight time constraints. In this book Teri helps us understand the better questions we should be asking about our data, data systems, networks, architecture development, vendors and cybersecurity writ large and why the answers to these questions matter to our organizations bottom line as well as our personal liability. Teri writes in a conversational tone adding personal experiences that bring life and ease of understanding to an otherwise very technical, complex and sometimes overwhelming subject. Each chapter breaks down a critical component that lends to a comprehensive understanding or can be taken individually. I am not steeped in cyber but Teri’s advice and recommendations have proven critical to my own work on Boards of Directors as well as my leadership work with corporate CISOs, cybersecurity teams, and C-Suite executives. In a time constrained world this is a worthy read. Stephen A. Clark, Maj Gen, USAF (Ret) AUTHOR: Teri Radichel is the CEO of 2nd Sight Lab, a cloud and cybersecurity training and consulting company. She has a Master of Software Engineering, a Master of Information Security Engineering, and over 25 years of technology, security, and business experience. Her security certifications include GSE, GXPN, GCIH, GPEN, GCIA, GCPM, GCCC, and GREM. SANS Institute gave her the 2017 Difference Makers Award for innovation in cybersecurity. She is a member of the IANS (Institute for Applied Network Security) faculty and formerly taught and helped with curriculum for cloud security classes at SANS Institute.

    Once used chiefly to add interactivity to web browser windows, JavaScript is now a primary building block of powerful and robust applications. In this practical book, new and experienced JavaScript developers will learn how to use this language to create APIs as well as web, mobile, and desktop applications.Author and engineering leader Adam D. Scott covers technologies such as Node.js, GraphQL, React, React Native, and Electron. Ideal for developers who want to build full stack applications and ambitious web development beginners looking to bootstrap a startup, this book shows you how to create a single CRUD-style application that will work across several platforms.Explore GraphQL's simple process for querying dataLearn about shared authentication for APIs, web apps, and native applicationsBuild performant web applications with React and Styled ComponentsUse React Native to write cross-platform applications for iOS and Android that compile to native codeLearn how to write desktop applications with Electron

    

    Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition.Summary Computer vision is central to many leading-edge innovations, including self-driving cars, drones, augmented reality, facial recognition, and much, much more. Amazing new computer vision applications are developed every day, thanks to rapid advances in AI and deep learning (DL). Deep Learning for Vision Systems teaches you the concepts and tools for building intelligent, scalable computer vision systems that can identify and react to objects in images, videos, and real life. With author Mohamed Elgendy's expert instruction and illustration of real-world projects, you’ll finally grok state-of-the-art deep learning techniques, so you can build, contribute to, and lead in the exciting realm of computer vision! Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology How much has computer vision advanced? One ride in a Tesla is the only answer you’ll need. Deep learning techniques have led to exciting breakthroughs in facial recognition, interactive simulations, and medical imaging, but nothing beats seeing a car respond to real-world stimuli while speeding down the highway. About the book How does the computer learn to understand what it sees? Deep Learning for Vision Systems answers that by applying deep learning to computer vision. Using only high school algebra, this book illuminates the concepts behind visual intuition. You'll understand how to use deep learning architectures to build vision system applications for image generation and facial recognition. What's inside     Image classification and object detection     Advanced deep learning architectures     Transfer learning and generative adversarial networks     DeepDream and neural style transfer     Visual embeddings and image search About the reader For intermediate Python programmers. About the author Mohamed Elgendy is the VP of Engineering at Rakuten. A seasoned AI expert, he has previously built and managed AI products at Amazon and Twilio. Table of Contents PART 1 - DEEP LEARNING FOUNDATION 1 Welcome to computer vision 2 Deep learning and neural networks 3 Convolutional neural networks 4 Structuring DL projects and hyperparameter tuning PART 2 - IMAGE CLASSIFICATION AND DETECTION 5 Advanced CNN architectures 6 Transfer learning 7 Object detection with R-CNN, SSD, and YOLO PART 3 - GENERATIVE MODELS AND VISUAL EMBEDDINGS 8 Generative adversarial networks (GANs) 9 DeepDream and neural style transfer 10 Visual embeddings

    Built on the fundamentals of penetration testing, Red Teaming uses a comprehensive approach to gain insight into an organization’s overall security to test its ability to detect, respond to, and recover from an attack. When properly conducted, Red Team activities significantly improve an organization’s security controls, help hone defensive capabilities, and measure the effectiveness of security operations.The Red Team concept requires a different approach from a typical security testing and relies heavily on well-defined TTPs, which are critical to successfully emulating a realistic threat or adversary. Red Team results exceed a typical list of penetration test vulnerabilities, provide a deeper understanding of how an organization would perform against an actual threat, and identify where security strengths and weaknesses exist. Whether you support a defensive or offensive role in security, understanding how Red Teams can be used to improve security is extremely valuable. Organizations spend a great deal of time and money on the security of their systems, and it is critical to have professionals who can effectively and efficiently operate them. This book will provide you with the skills to manage and operate a Red Team, conduct Red Team engagements, and understand the role of a Red Team and its importance in security testing.

    

    This step-by-step book educates manufacturers about the implementation of security best practices in accord with industry standards and expectations, advising the reader about everything from high-level concepts to real-world solutions and tools. It walks the reader through the security aspects of every lifecycle phase of the product, including concept; design; implementation; supply chain; manufacturing; postmarket; maintenance; and end of life. It details the practices, processes, and outputs necessary to create a secure medical device capable of gaining regulatory approval and meeting market entry requirements. This book equips medical device manufacturers with the knowledge and capability required to produce secure products that anticipate healthcare delivery organizations’ (HDOs) and patients’ needs and expectations, meet market-entry requirements set by regulators and standards organizations, and reduce patient, HDO, and manufacturer exposure to increasingly sophisticated cyber adversaries. It explores the differences between cybersecurity in an IT/MIS environment versus the application and management of cybersecurity during the development of an embedded product, as typically found in the medical device ecosystem. Designers and manufacturers learn how to mitigate or avoid common cybersecurity vulnerabilities frequently introduced during development and production. It details regulatory and customer expectations for documentation artifacts and deliverables that demonstrate cybersecurity compliance and features as well as regulator expectations for postmarket activities during device service life. Readers become aware of the growing sophistication of cyber adversaries disproportionate to industry understanding of cybersecurity exposure and potential impacts.

    Whether you’ve had any prior programming experience or not, the tutorials on this site will walk you through all the steps to write, compile, and debug your C++ programs, all with plenty of examples.Becoming an expert won’t happen overnight, but with a little patience, you’ll get there. And LearnCpp.com will show you the way.

    James Stewart's Calculus series is the top-seller in the world because of its problem-solving focus, mathematical precision and accuracy, and outstanding examples and problem sets. Selected and mentored by Stewart, coauthors Daniel Clegg and Saleem Watson continue his legacy, and their careful refinements retain Stewart's clarity of exposition and make the 9th Edition an even more usable learning tool. The accompanying WebAssign includes helpful learning support and new resources like Explore It interactive learning modules. Showing that Calculus is both practical and beautiful, the Stewart approach and WebAssign resources enhance understanding and build confidence for millions of students worldwide.

    

    You'll find learning objectives at the beginning of each chapter, exam tips, in-depth explanations, and practice exam questions. All questions closely mirror those on the actual test in content, format, and tone. Designed to help you pass the CS0-002 exam with ease, this definitive guide also serves as an essential on-the-job reference.Covers all exam topics, including: Threat and vulnerability managementThreat data and intelligenceVulnerability management, assessment tools, and mitigationSoftware and systems securitySolutions for infrastructure managementSoftware and hardware assurance best practicesSecurity operations and monitoringProactive threat huntingAutomation concepts and technologiesIncident response process, procedure, and analysisCompliance and assessmentData privacy and protectionSupport of organizational risk mitigationOnline content includes: 200+ practice questionsInteractive performance-based questionsTest engine that provides full-length practice exams and customizable quizzes by exam objective

    The book emphasizes how to strike a difficult balance between establishing a new (digital) business and re-vitalizing - and digitizing - the legacy business.The core of the book is focused on the actual implementation of the digital transformation across both businesses, providing concrete tips, tricks, tools and action plans across six key dimensions:Crafting a flexible organization Using technology as a driver Designing the necessary processes Building transformational leaders "Right-skilling" the workforce of the future Galvanizing cultural change The Digital Transformer's Dilemma is a very visual book, filled with dozens of engaging illustrations that bring the contained concepts to life on the page.Based on 100+ interviews with senior executives at leading companies (such as Nestl�, Novartis, Volkswagen, BNP Paribas, BASF and Michelin) and smaller hidden champions, numerous illuminating case studies, and the authors' own experience from working in international management consulting and years of academic experience, the book highlights the fundamental principles required for executives and businesspeople to transform legacy organizations into digitally empowered companies.

    Readers dig deep into technical (and related legal) issues, as they learn what kinds of devices to use as hacking tools and which make the best targets. The authors, all experts in the field, cover the kinds of vulnerabilities found in IoT devices, explain how to exploit their network protocols, and how to leverage security flaws and certain hardware interfaces found in the physical devices themselves.The book begins with threat modeling and a security testing methodology, then covers how to attack hardware interfaces such as UART, I�C, SPI, JTAG / SWD and IoT network protocols like UPnP, WS-Discovery, mDNS, DNS-SD, RTSP / RTCP / RTP, LoRa / LoRaWAN, Wi-Fi / Wi-Fi Direct, RFID / NFC, BLE, MQTT, CDP and DICOM. Examples throughout offer custom code designed to demonstrate specific vulnerabilities and tools to help readers reproduce the attacks. Practical IoT Hacking is full of practical exercises and hands-on examples taken from the authors' own research that teach readers things like how to bypass the authentication of an STM32F103 device (black pill) through SWD; reverse firmware; exploit zero-configuration networking; use low-cost equipment to capture LoRa network traffic; analyze IoT companion mobile apps, take over and remotely control an Android based treadmill, jam wireless devices such as home alarm systems, hijack Bluetooth Low Energy connections and how to circumvent modern RFID and NFC enabled smart door locks.

    Learn the tricks of automation before it is too late and let’s rebuild together the partially de-globalized world during and in the aftermath of the Covid-19 Outbreak.

    

    

    Python is the ideal language for network engineers to explore tools that were previously available to systems engineers and application developers. In Mastering Python Networking, Third edition, you’ll embark on a Python-based journey to transition from traditional network engineers to network developers ready for the next-generation of networks.This new edition is completely revised and updated to work with Python 3. In addition to new chapters on network data analysis with ELK stack (Elasticsearch, Logstash, Kibana, and Beats) and Azure Cloud Networking, it includes updates on using newer libraries such as pyATS and Nornir, as well as Ansible 2.8. Each chapter is updated with the latest libraries with working examples to ensure compatibility and understanding of the concepts.Starting with a basic overview of Python, the book teaches you how it can interact with both legacy and API-enabled network devices. You will learn to leverage high-level Python packages and frameworks to perform network automation tasks, monitoring, management, and enhanced network security followed by Azure and AWS Cloud networking. Finally, you will use Jenkins for continuous integration as well as testing tools to verify your network. What you will learn Use Python libraries to interact with your network Integrate Ansible 2.8 using Python to control Cisco, Juniper, and Arista network devices Leverage existing Flask web frameworks to construct high-level APIs Learn how to build virtual networks in the AWS & Azure Cloud Learn how to use Elastic Stack for network data analysis Understand how Jenkins can be used to automatically deploy changes in your network Use PyTest and Unittest for Test-Driven Network Development in networking engineering with Python Who this book is for Mastering Python Networking, Third edition is for network engineers, developers, and SREs who want to use Python for network automation, programmability, and data analysis. Basic familiarity with Python programming and networking-related concepts such as Transmission Control Protocol/Internet Protocol (TCP/IP) will be useful. Table of Contents Review of TCP/IP Protocol Suite and Python Low-Level Network Device Interactions APIs and Intent-Driven Networking The Python Automation Framework – Ansible Basics The Python Automation Framework – Beyond Basics Network Security with Python Network Monitoring with Python – Part 1 Network Monitoring with Python – Part 2 Building Network Web Services with Python AWS Cloud Networking Azure Cloud Networking Network Data Analysis with Elastic Stack Working with Git

    With the open-source release of this formerly restricted tool suite, one of the world's most capable disassemblers and intuitive decompilers is now in the hands of cybersecurity defenders everywhere -- and The Ghidra Book is the one and only guide you need to master it.In addition to discussing RE techniques useful in analyzing software and malware of all kinds, the book thoroughly introduces Ghidra's components, features, and unique capacity for group collaboration. You'll learn how to:• Navigate a disassembly• Use Ghidra's built-in decompiler to expedite analysis• Analyze obfuscated binaries• Extend Ghidra to recognize new data types• Build new Ghidra analyzers and loaders• Add support for new processors and instruction sets• Script Ghidra tasks to automate workflows• Set up and use a collaborative reverse engineering environmentDesigned for beginner and advanced users alike, The Ghidra Book will effectively prepare you to meet the needs and challenges of RE, so you can analyze files like a pro.

    It introduces fundamental concepts such as classes and labels, building a dataset, and what a model is and does before presenting classic machine learning models, neural networks, and modern convolutional neural networks. Experiments in Python--working with leading open-source toolkits and standard datasets--give the reader hands-on experience with each model and help them build intuition about how to transfer the examples in the book to their own projects.Readers start with an introduction to the Python language and the NumPy extension that is ubiquitous in machine learning. Prominent toolkits, like sklearn and Keras/TensorFlow are used as the backbone to enable readers to focus on the elements of machine learning without the burden of writing implementations from scratch. An entire chapter on evaluating the performance of models gives the reader the knowledge necessary to understand claims on performance and to know which models are working well and which are not. The book culminates by presenting convolutional neural networks as an introduction to modern deep learning. Understanding how these networks work and how they are affected by parameter choices leaves the reader with the core knowledge necessary to dive into the larger, ever-changing world of deep learning.

    

    Applied Incident Response details effective ways to respond to advanced attacks against local and remote network resources, providing proven response techniques and a framework through which to apply them. As a starting point for new incident handlers, or as a technical reference for hardened IR veterans, this book details the latest techniques for responding to threats against your network, including:Preparing your environment for effective incident response Leveraging MITRE ATT&CK and threat intelligence for active network defense Local and remote triage of systems using PowerShell, WMIC, and open-source tools Acquiring RAM and disk images locally and remotely Analyzing RAM with Volatility and Rekall Deep-dive forensic analysis of system drives using open-source or commercial tools Leveraging Security Onion and Elastic Stack for network security monitoring Techniques for log analysis and aggregating high-value logs Static and dynamic analysis of malware with YARA rules, FLARE VM, and Cuckoo Sandbox Detecting and responding to lateral movement techniques, including pass-the-hash, pass-the-ticket, Kerberoasting, malicious use of PowerShell, and many more Effective threat hunting techniques Adversary emulation with Atomic Red Team Improving preventive and detective controls

    Written by Cisco experts based on Cisco's own internal training, it clearly explains the value of each technique, presents realistic use cases, introduces solution components, illuminates their inner workings, and shows how to execute on what you've learned in practice. Designed for all Cisco DevNet Associate candidates, it covers every DEVASC 200-901 objective concisely and logically, with extensive teaching features designed to promote retention and understanding. You'll find: Pre-chapter quizzes to assess knowledge upfront and focus your study more efficiently Foundation topics sections that explain concepts and configurations, and link theory to practice Key topics sections calling attention to every figure, table, and list you must know Exam Preparation sections with additional chapter review features Final preparation chapter providing tools and a complete final study plan A customizable practice test library This guide offers comprehensive, up-to-date coverage of all DEVASC 200-901 topics related to: Software development and design Understanding and using APIs Cisco platforms and development Application deployment and security Infrastructure and automation Network fundamentals

    Anyone caught breaking the rules or trying to manipulate rankings through aggressive SEO techniques, will find their website dropping out of the top 10, top 100, or out of the search results altogether. Commonly taught SEO techniques can now kill your rankings! Google released a whole menagerie of animals (Panda, Penguin, Pigeon, etc), but also employs humans to rate your content. You cannot fly under the radar any more. Gone are the days of fast rankings with SEO loopholes. Today, SEO can be dangerous if you follow the wrong advice. Most free online SEO advice is very wrong because it's either out of date, or written by someone that doesn't do it for a living. I've been studying, testing, and teaching SEO for over a decade. SEO 2020 is a book that will teach you the safe, white-hat search engine optimization strategies I personally use to get my web pages (and those of my clients) to rank high in Google. This is battle-tested, white hat SEO that I've learned, developed and tested over the last decade. On-site optimization techniques that I was teaching my newsletter readers back in 2008, are only now becoming mainstream in SEO. I play by Google's rules, meaning I never have to wake up after a major update and wonder if my sites have been hit. With so many algorithm changes taking place at Google, you might be wondering how it is possible to stay up to date with all the changes. The good news is that it is easy once you acquire the right mindset. Understand what Google is trying to do, and give it to them. You won't find me discussing loopholes or strategies to beat the system. What you will find is solid strategies & advice to create great content, build authority links, and increase your domain authority. This book covers everything you need to know, including: What is SEO and what are the main rnaking factors? Major Google changes and how they have affected the way we do SEO. Creating the quality content your visitors want, and search engines love. Finding essential theme words and phrases for any piece of content you write. All on-page factors discussed. Scema & Structured data. Site organization & structure. What is authority, and how you can you incrase yours? How to get authority, white-hat, high quality backlinks. Giving your visitors what they want, while keeping search engines happy. A complete SEO audit to check for common problems. SEO 2020 was written by search engine veteran Andy Williams of ezSEONews.com. He has been teaching this stuff since 2003, in his free weekly newsletter. If you want to understand what the search engines want, and learn modern search engine optimization that gets higher rankings through great content and smart backlinking, explode your traffic, AND have Google's blessing, then you should read this book.

    Now in its third edition, this book focuses on practical algorithms for mining data from even the largest datasets.

    Computer Graphics from Scratch aims to demystify these algorithms and show readers that computer graphics can be surprisingly simple. This broad introductory book gives readers an overview of the computer graphics field with a focus on two core areas of modern graphics: raytracing and rasterization. Links to interactive demos throughout bring the algorithms alive. Every algorithm is built up without the use of external libraries or APIs and is presented with language agnostic pseudocode, allowing anyone with a basic understanding of programming and high school math to follow along.

    While discounted in some circles as derivative and consigned to perpetual catch-up mode, China's hybrid system of legal, illegal, and extralegal import of foreign technology, combined with its indigenous efforts, is, the authors believe, enormously effective and must be taken seriously. Accordingly, in this volume, 17 international specialists combine their scholarship to portray the system's structure and functioning in heretofore unseen detail, using primary Chinese sources to demonstrate the perniciousness of the problem in a manner not likely to be controverted. The book concludes with a series of recommendations culled from the authors' interactions with experts worldwide.This book will be of much interest to students of Chinese politics, US foreign policy, intelligence studies, science and technology studies, and International Relations in general.

    Based on the author's twenty years of teaching physics and engineering, this intuitive guide to Newton's laws of motion corrects the many misconceptions surrounding this fundamental topic. Adopting an informal and pedagogical approach and a clear, accessible style, this concise text presents Newton's laws in a coherent story of force and motion. Carefully scaffolded everyday examples and full explanations of concepts and equations ensure that all students studying physics develop a deep understanding of Newton's laws of motion. Fully worked solutions to the exercises are available on the book's webpage.

    But as the world of business becomes more interconnected and global, enterprise data is no long a monolith; it is just a part of a vast web of data. Managing data on a world-wide scale is a key capability for any business today.The Semantic Web treats data as a distributed resource on the scale of the World Wide Web, and incorporates features to address the challenges of massive data distribution as part of its basic design. The aim of the first two editions was to motivate the Semantic Web technology stack from end-to-end; to describe not only what the Semantic Web standards are and how they work, but also what their goals are and why they were designed as they are. It tells a coherent story from beginning to end of how the standards work to manage a world-wide distributed web of knowledge in a meaningful way.The third edition builds on this foundation to bring Semantic Web practice to enterprise. Fabien Gandon joins Dean Allemang and Jim Hendler, bringing with him years of experience in global linked data, to open up the story to a modern view of global linked data. While the overall story is the same, the examples have been brought up to date and applied in a modern setting, where enterprise and global data come together as a living, linked network of data. Also included with the third edition, all of the data sets and queries are available online for study and experimentation at data.world/swwo.

    

    In the beginning, there may be little or no data to work with. At this point, a basic solution that uses rule based systems or traditional machine learning will be apt. As you accumulate more data, more sophisticated--and often data intensive--ML techniques can be used including deep learning. At each step of this journey, there are dozens of alternative approaches you can take. This book helps you navigate this maze of options.

    

    Written by an Oracle expert and respected author, Oracle Cloud Infrastructure Architect Associate All-in-One Exam Guide (Exam 1Z0-1072) offers complete coverage of every subject on the challenging exam. Hands-on exercises, practice exam questions with in-depth explanations, “Notes,” “Exam Tips,” and “Cautions” throughout provide professional insight and call out potentially harmful situations. Beyond exam preparation, this guide also serves as a valuable on-the-job reference. Covers all exam topics, including:• Oracle Cloud Infrastructure concepts• OCI identity and access management• OCI networking• Compute instances• Storage• Database• Automation tools• OCI best practice architectures Online content includes:• 140 practice questions• Fully-customizable online test engine

    This book will show you how to blend Django, a high-level Python Web framework, with Django REST, the powerful, feature-filled extension, to build iOS mobile apps.Using easy-to-follow examples, you'll begin by building a simple app using the RESTful Web API and iOS. You'll begin by using traditional Django to create models and connect your App to the database. You'll then see how to serialize your data and create the RESTful API. The second part of the book introduces Xcode, a programming environment to develop iOS apps. Using Swift, the programming language for iOS, you'll design the actual app. Once you have your back-end in Django and a front-end in Swift, you'll connect them using our RESTful API. You'll be able to log in, browse places of interest, and rate them and leave comments. Guided step-by-step instructions, Building Versatile Mobile Apps with Python and REST will demonstrate how easy it is to use Python to develop iOS applications. What You'll LearnBuild Create-Read-Update-Delete functionality using RESTful Web Services Incorporate marketing into the design of iOS apps to stand out in the App Store Deploy your app to a live server and add it to Apple app store Who This Book Is ForAspiring programmers who want to develop modern RESTful Web Services and design the front-end for iOS. Developers who want to combine the most powerful and popular back-end technology—Python—and monetize it with a popular iOS platform in Apple App Store.

    

    

    By learning how to build and deploy scalable model pipelines, data scientists can own more of the model production process and more rapidly deliver data products. This book provides a hands-on approach to scaling up Python code to work in distributed environments in order to build robust pipelines. Readers will learn how to set up machine learning models as web endpoints, serverless functions, and streaming pipelines using multiple cloud environments. It is intended for analytics practitioners with hands-on experience with Python libraries such as Pandas and scikit-learn, and will focus on scaling up prototype models to production. From startups to trillion dollar companies, data science is playing an important role in helping organizations maximize the value of their data. This book helps data scientists to level up their careers by taking ownership of data products with applied examples that demonstrate how to: Translate models developed on a laptop to scalable deployments in the cloud Develop end-to-end systems that automate data science workflows Own a data product from conception to production The accompanying Jupyter notebooks provide examples of scalable pipelines across multiple cloud environments, tools, and libraries (github.com/bgweber/DS_Production). Book Contents Here are the topics covered by Data Science in Production: Chapter 1: Introduction - This chapter will motivate the use of Python and discuss the discipline of applied data science, present the data sets, models, and cloud environments used throughout the book, and provide an overview of automated feature engineering. Chapter 2: Models as Web Endpoints - This chapter shows how to use web endpoints for consuming data and hosting machine learning models as endpoints using the Flask and Gunicorn libraries. We'll start with scikit-learn models and also set up a deep learning endpoint with Keras. Chapter 3: Models as Serverless Functions - This chapter will build upon the previous chapter and show how to set up model endpoints as serverless functions using AWS Lambda and GCP Cloud Functions. Chapter 4: Containers for Reproducible Models - This chapter will show how to use containers for deploying models with Docker. We'll also explore scaling up with ECS and Kubernetes, and building web applications with Plotly Dash. Chapter 5: Workflow Tools for Model Pipelines - This chapter focuses on scheduling automated workflows using Apache Airflow. We'll set up a model that pulls data from BigQuery, applies a model, and saves the results. Chapter 6: PySpark for Batch Modeling - This chapter will introduce readers to PySpark using the community edition of Databricks. We'll build a batch model pipeline that pulls data from a data lake, generates features, applies a model, and stores the results to a No SQL database. Chapter 7: Cloud Dataflow for Batch Modeling - This chapter will introduce the core components of Cloud Dataflow and implement a batch model pipeline for reading data from BigQuery, applying an ML model, and saving the results to Cloud Datastore. Chapter 8: Streaming Model Workflows - This chapter will introduce readers to Kafka and PubSub for streaming messages in a cloud environment.

    Its opinionated design and built-in concurrency features make it easy for engineers to author code that efficiently utilizes all available CPU cores.This Golang book distills industry best practices for writing lean Go code that is easy to test and maintain, and helps you to explore its practical implementation by creating a multi-tier application called Links ‘R’ Us from scratch. You’ll be guided through all the steps involved in designing, implementing, testing, deploying, and scaling an application. Starting with a monolithic architecture, you’ll iteratively transform the project into a service-oriented architecture (SOA) that supports the efficient out-of-core processing of large link graphs. You’ll learn about various cutting-edge and advanced software engineering techniques such as building extensible data processing pipelines, designing APIs using gRPC, and running distributed graph processing algorithms at scale. Finally, you’ll learn how to compile and package your Go services using Docker and automate their deployment to a Kubernetes cluster.By the end of this book, you’ll know how to think like a professional software developer or engineer and write lean and efficient Go code. What you will learn Understand different stages of the software development life cycle and the role of a software engineer Create APIs using gRPC and leverage the middleware offered by the gRPC ecosystem Discover various approaches to managing package dependencies for your projects Build an end-to-end project from scratch and explore different strategies for scaling it Develop a graph processing system and extend it to run in a distributed manner Deploy Go services on Kubernetes and monitor their health using Prometheus Who this book is for This Golang programming book is for developers and software engineers looking to use Go to design and build scalable distributed systems effectively. Knowledge of Go programming and basic networking principles is required. Table of Contents A Bird's-Eye View of Software Engineering Best Practices for Writing Clean and Maintainable Go Code Dependency Management The Art of Testing The Links 'R' Us Project Building a Persistence Layer Data-Processing Pipelines Graph-Based Data Processing Communicating with the Outside World Building, Packaging, and Deploying Software Splitting Monoliths into Microservices Building Distributed Graph-Processing Systems Metrics Collection and Visualization Epilogue

    This book, complete with practice questions and answers, forms a course which will take you from beginner or intermediate level to having a confident grasp of physics. The book includes: simple step-by-step explanations, to help you grasp new topics or those that have previously confused you; practice questions throughout, to help you embed your learning and improve your confidence; and end of chapter summaries to help you remember the key points you've learnt - all in one great-value book, so you don't need any separate workbooks or course books. Chapters include: Starting physics, motion, forces in action, thermal physics, engines and thermodynamics, electricity, the nature of light, materials and molecules, quantum theory and relativity, the structure of matter, nuclear energy, space and the universe, and the frontiers of physics. The Complete Introduction series from Teach Yourself is the ultimate one-stop guide for anyone wanting a comprehensive and accessible entry point into subjects as diverse as philosophy, mathematics, psychology, economics and practical electronics. Loved by students and perfect for general readers who simply want to learn more about the world around them, these books are your first choice for discovering something new.

    SEO is not merely trying to improve your website ranking on Google, but it can spark and optimize ideas. This book provides you with a comprehensive approach to make sure marketing spend is utilized as effectively as possible and deliver the best ROI for your brand and business.Maximizing your organic (free) traffic channels should be a top priority and this book will provide you with insight on how to do that. From working with social media influencers to steering creative ideas and campaigns, modern day SEO requires a full-service perspective of marketing and its processes.- Learn current SEO algorithms and practices that impact Search Engine Optimization- Find out why content diversity is important- Discover how brands are ineffectively executing SEO strategies and what they can do to change and improve their results- Break out beyond the traditional search engines and look at other critical content venues like Amazon and YouTubeIn addition to learning the most effective processes to structure your SEO, you will have access to bonus materials that accompany this book which will include worksheets, checklists, creative brief examples, quizzes, and best interview questions when hiring an SEO specialist. Modern-day marketers, business owners, and brand managers, this book is for you!