The book will teach you about the most important services on AWS. You will also learn about best practices regarding automation, security, high availability, and scalability.Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologyPhysical data centers require lots of equipment and take time and resources to manage. If you need a data center, but don't want to build your own, Amazon Web Services may be your solution. Whether you're analyzing real-time data, building software as a service, or running an e-commerce site, AWS offers you a reliable cloud-based platform with services that scale. All services are controllable via an API which allows you to automate your infrastructure.About the BookAmazon Web Services in Action introduces you to computing, storing, and networking in the AWS cloud. The book will teach you about the most important services on AWS. You will also learn about best practices regarding security, high availability and scalability.You'll start with a broad overview of cloud computing and AWS and learn how to spin-up servers manually and from the command line. You'll learn how to automate your infrastructure by programmatically calling the AWS API to control every part of AWS. You will be introduced to the concept of Infrastructure as Code with the help of AWS CloudFormation.You will learn about different approaches to deploy applications on AWS. You'll also learn how to secure your infrastructure by isolating networks, controlling traffic and managing access to AWS resources. Next, you'll learn options and techniques for storing your data. You will experience how to integrate AWS services into your own applications by the use of SDKs. Finally, this book teaches you how to design for high availability, fault tolerance, and scalability.What's InsideOverview of cloud concepts and patternsManage servers on EC2 for cost-effectivenessInfrastructure automation with Infrastructure as Code (AWS CloudFormation)Deploy applications on AWSStore data on AWS: SQL, NoSQL, object storage and block storageIntegrate Amazon's pre-built servicesArchitect highly available and fault tolerant systemsAbout the ReaderWritten for developers and DevOps engineers moving distributed applications to the AWS platform.About the AuthorsAndreas Wittig and Michael Wittig are software engineers and consultants focused on AWS and web development.Table of ContentsPART 1 GETTING STARTEDWhat is Amazon Web Services?A simple example: WordPress in five minutesPART 2 BUILDING VIRTUAL INFRASTRUCTURE WITH SERVERS AND NETWORKINGUsing virtual servers: EC2Programming your infrastructure: the command line, SDKs, and CloudFormationAutomating deployment: CloudFormation, Elastic Beanstalk, and OpsWorksSecuring your system: IAM, security groups, and VPCPART 3 STORING DATA IN THE CLOUDStoring your objects: S3 and GlacierStoring your data on hard drives: EBS and instance storeUsing a relational database service: RDSProgramming for the NoSQL database service: DynamoDBPART 4 ARCHITECTING ON AWSAchieving high availability: availability zones, auto-scaling, and CloudWatchDecoupling your infrastructure: ELB and SQSDesigning for fault-toleranceScaling up and down: auto-scaling and CloudWatch

    It is suitable for a one or two semester university course on AI, as well as for researchers in the field.

    Another AI discovered a new antibiotic by analyzing molecular properties human scientists did not understand. Now, AI-powered jets are defeating experienced human pilots in simulated dogfights. AI is coming online in searching, streaming, medicine, education, and many other fields and, in so doing, transforming how humans are experiencing reality.In The Age of AI, three leading thinkers have come together to consider how AI will change our relationships with knowledge, politics, and the societies in which we live. The Age of AI is an essential roadmap to our present and our future, an era unlike any that has come before.

    This causes real problems for everyday users who need to make sense of all the information available, and for software engineers who want to make their text-based applications more useful and user-friendly. Whether building a search engine for a corporate website, automatically organizing email, or extracting important nuggets of information from the news, dealing with unstructured text can be daunting.Taming Text is a hands-on, example-driven guide to working with unstructured text in the context of real-world applications. It explores how to automatically organize text, using approaches such as full-text search, proper name recognition, clustering, tagging, information extraction, and summarization. This book gives examples illustrating each of these topics, as well as the foundations upon which they are built.Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

    

    It's a beautifully written tutorial that begins with the basic steps to get your first Ruby program up and running and goes on to explore sophisticated topics like callable objects, reflection, and threading. Whether the topic is simple or tough, the book's easy-to-follow examples and explanations will give you immediate confidence as you build your Ruby programming skills.The Well-Grounded Rubyist is a thoroughly revised and updated edition of the best-selling Ruby for Rails. In this new book, expert author David A. Black moves beyond Rails and presents a broader view of Ruby. It covers Ruby 1.9, and keeps the same sharp focus and clear writing that made Ruby for Rails stand out.Starting with the basics, The Well-Grounded Rubyist explains Ruby objects and their interactions from the ground up. In the middle chapters, the book turns to an examination of Ruby's built-in, core classes, showing the reader how to manipulate strings, numbers, arrays, ranges, hashes, sets, and more. Regular expressions get attention, as do file and other I/O operations.Along the way, the reader is introduced to numerous tools included in the standard Ruby distribution--tools like the task manager Rake and the interactive Ruby console-based interpreter Irb--that facilitate Ruby development and make it an integrated and pleasant experience.The book encompasses advanced topics, like the design of Ruby's class and module system, and the use of Ruby threads, taking even the new Rubyist deep into the language and giving every reader the foundations necessary to use, explore, and enjoy this unusually popular and versatile language.It's no wonder one reader commented: "The technical depth is just right to not distract beginners, yet detailed enough for more advanced readers."Purchase of the print book comes with an offer of a free PDF, ePub, and Kindle eBook from Manning. Also available is all code from the book.

    Non- mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics. Dr. Kuhn is a Director of Non-Clinical Statistics at Pfizer Global R&D in Groton Connecticut. He has been applying predictive models in the pharmaceutical and diagnostic industries for over 15 years and is the author of a number of R packages. Dr. Johnson has more than a decade of statistical consulting and predictive modeling experience in pharmaceutical research and development. He is a co-founder of Arbor Analytics, a firm specializing in predictive modeling and is a former Director of Statistics at Pfizer Global R&D. His scholarly work centers on the application and development of statistical methodology and learning algorithms. Applied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. Addressing practical concerns extends beyond model fitting to topics such as handling class imbalance, selecting predictors, and pinpointing causes of poor model performance-all of which are problems that occur frequently in practice. The text illustrates all parts of the modeling process through many hands-on, real-life examples. And every chapter contains extensive R code f

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    For Eli Miller, it was never a choice.Most of Eli’s life has been spent running, doing everything in his power to protect his family. His world is plagued by war, wild magic, and unimaginable monsters. But none of these threats are more dangerous than the immortal beings known as Adventurers. They are players and Entarra is their game. Its citizens aren’t real. Yet, to the billions of near-sentient AI that live there, the game world is the only one they will ever know. It is where they are born, live, and die. Eli is no different. After being attacked with a strange weapon, Eli awakens as the thing he fears most: an adventurer. Struggling to cope with his new reality, he finds himself in the middle of the most nefarious plot of all: His world, and everything he loves, is about to be deleted.

    His aim is to present calculus as the first real encounter with mathematics: it is the place to learn how logical reasoning combined with fundamental concepts can be developed into a rigorous mathematical theory rather than a bunch of tools and techniques learned by rote. Since analysis is a subject students traditionally find difficult to grasp, Spivak provides leisurely explanations, a profusion of examples, a wide range of exercises and plenty of illustrations in an easy-going approach that enlightens difficult concepts and rewards effort. Calculus will continue to be regarded as a modern classic, ideal for honours students and mathematics majors, who seek an alternative to doorstop textbooks on calculus, and the more formidable introductions to real analysis.

    This Fourth Edition not only keeps this tradition alive, it actually improves on it."--Steve Vinoski, Chief Engineer, Product Innovation, IONA Technologies" The Primer really brings this large and complex language down to size."--Justin Shaw, Senior Member of Technical Staff, Electronic Programs Division, The Aerospace Corporation"It not only gets novices up and running early, but gets them to do so using good programming practices."--Nevin ": -)" Liber, Senior Principal Engineer (C++ developer since 1988)This popular tutorial introduction to standard C++ has been completely updated, reorganized, and rewritten to help programmers learn the language faster and use it in a more modern, effective way.Just as C++ has evolved since the last edition, so has the authors' approach to teaching it. They now introduce the C++ standard library from the beginning, giving readers the means to write useful programs without first having to master every language detail. Highlighting today's best practices, they show how to write programs that are safe, can be built quickly, and yet offer outstanding performance. Examples that take advantage of the library, and explain the features of C++, also show how to make the best use of the language. As in its previous editions, the book's authoritative discussion of fundamental C++ concepts and techniques makes it a valuable resource even for more experienced programmers.Program Faster and More Effectively with This Rewritten ClassicRestructured for quicker learning, using the C++ standard libraryUpdated to teach the most current programming styles and program design techniquesFilled with new learning aids that emphasize important points, warn about common pitfalls, suggest good programming practices, and provide general usage tipsComplete with exercises that reinforce skills learnedAuthoritative and comprehensive in its coverage The source code for the book's extended examples is available on the Web at the address below.www.awprofessional.com/cpp_primer

    This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915            0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)

    The manner in which computers are now able to mimic human thinking is rapidly exceeding human capabilities in everything from chess to picking the winner of a song contest. In the age of machine learning, computers do not strictly need to receive an ‘input command’ to perform a task, but rather ‘input data’. From the input of data they are able to form their own decisions and take actions virtually as a human would. But as a machine, can consider many more scenarios and execute calculations to solve complex problems. This is the element that excites companies and budding machine learning engineers the most. The ability to solve complex problems never before attempted. This is also perhaps one reason why you are looking at purchasing this book, to gain a beginner's introduction to machine learning. This book provides a plain English introduction to the following topics: - Artificial Intelligence - Big Data - Downloading Free Datasets - Regression - Support Vector Machine Algorithms - Deep Learning/Neural Networks - Data Reduction - Clustering - Association Analysis - Decision Trees - Recommenders - Machine Learning Careers This book has recently been updated following feedback from readers. Version II now includes: - New Chapter: Decision Trees - Cleanup of minor errors

    This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making.Understand how data science fits in your organization—and how you can use it for competitive advantageTreat data as a business asset that requires careful investment if you’re to gain real valueApproach business problems data-analytically, using the data-mining process to gather good data in the most appropriate wayLearn general concepts for actually extracting knowledge from dataApply data science principles when interviewing data science job candidates

    It's as if we think of code as a magic spell, an incantation to reveal what we need to know and even what we want. Humans have always believed that certain invocations—the marriage vow, the shaman's curse—do not merely describe the world but make it. Computation casts a cultural shadow that is shaped by this long tradition of magical thinking. In this book, Ed Finn considers how the algorithm—in practical terms, “a method for solving a problem”—has its roots not only in mathematical logic but also in cybernetics, philosophy, and magical thinking.Finn argues that the algorithm deploys concepts from the idealized space of computation in a messy reality, with unpredictable and sometimes fascinating results. Drawing on sources that range from Neal Stephenson's Snow Crash to Diderot's Encyclopédie, from Adam Smith to the Star Trek computer, Finn explores the gap between theoretical ideas and pragmatic instructions. He examines the development of intelligent assistants like Siri, the rise of algorithmic aesthetics at Netflix, Ian Bogost's satiric Facebook game Cow Clicker, and the revolutionary economics of Bitcoin. He describes Google's goal of anticipating our questions, Uber's cartoon maps and black box accounting, and what Facebook tells us about programmable value, among other things.If we want to understand the gap between abstraction and messy reality, Finn argues, we need to build a model of “algorithmic reading” and scholarship that attends to process, spearheading a new experimental humanities.