In the tradition of Manning's ground breaking "In Action" series, this book comes from right from the source. Written by Bruce Payette, one of principal creators of PowerShell, Windows PowerShell in Action shows you how to build scripts and utilities to automate system tasks or create powerful system management tools to handle the day-to-day tasks that drive a Windows administrator's life. Because it's based on the .NET platform, PowerShell is also a powerful tool for developers and power users.Windows PowerShell in Action was written by Bruce Payette, one of the founding members of the Windows PowerShell team, co-designer of the PowerShell language and the principal author of the PowerShell language implementation. The book enables you to get the most out of the PowerShell environment. Using many examples, both small and large, this book illustrates the features of the language and environment and shows how to compose those features into solutions, quickly and effectively.This book is designed for anyone who wants to learn PowerShell and use it well. Rather than simply being a book of recipes to read and apply, this book gives you the deep knowledge about how PowerShell works and how to apply it.

    How's that possible? Google revealed the secret through a project called Kubernetes, an open source cluster orchestrator (based on its internal Borg system) that radically simplifies the task of building, deploying, and maintaining scalable distributed systems in the cloud. This practical guide shows you how Kubernetes and container technology can help you achieve new levels of velocity, agility, reliability, and efficiency.Authors Kelsey Hightower, Brendan Burns, and Joe Beda--who've worked on Kubernetes at Google--explain how this system fits into the lifecycle of a distributed application. You will learn how to use tools and APIs to automate scalable distributed systems, whether it is for online services, machine-learning applications, or a cluster of Raspberry Pi computers.Explore the distributed system challenges that Kubernetes addressesDive into containerized application development, using containers such as DockerCreate and run containers on Kubernetes, using Docker's Image format and container runtimeExplore specialized objects essential for running applications in productionReliably roll out new software versions without downtime or errorsGet examples of how to develop and deploy real-world applications in Kubernetes

    It’s time we stand face-to-digital-face with the true powers and limitations of the algorithms that already automate important decisions in healthcare, transportation, crime, and commerce. Hello World is indispensable preparation for the moral quandaries of a world run by code, and with the unfailingly entertaining Hannah Fry as our guide, we’ll be discussing these issues long after the last page is turned.

    Not in an editor, IDE, or design tool. You're well educated on how to work with software and hardware, but what about wetware--our own brains? Learning new skills and new technology is critical to your career, and it's all in your head. In this book by Andy Hunt, you'll learn how our brains are wired, and how to take advantage of your brain's architecture. You'll learn new tricks and tips to learn more, faster, and retain more of what you learn. You need a pragmatic approach to thinking and learning. You need to Refactor Your Wetware. Programmers have to learn constantly; not just the stereotypical new technologies, but also the problem domain of the application, the whims of the user community, the quirks of your teammates, the shifting sands of the industry, and the evolving characteristics of the project itself as it is built. We'll journey together through bits of cognitive and neuroscience, learning and behavioral theory. You'll see some surprising aspects of how our brains work, and how you can take advantage of the system to improve your own learning and thinking skills.In this book you'll learn how to:Use the Dreyfus Model of Skill Acquisition to become more expertLeverage the architecture of the brain to strengthen different thinking modesAvoid common "known bugs" in your mindLearn more deliberately and more effectivelyManage knowledge more efficientlyPrinted in full color.

    

    You'll learn how to combine small, yet powerful, command-line tools to quickly obtain, scrub, explore, and model your data.To get you started--whether you're on Windows, OS X, or Linux--author Jeroen Janssens introduces the Data Science Toolbox, an easy-to-install virtual environment packed with over 80 command-line tools.Discover why the command line is an agile, scalable, and extensible technology. Even if you're already comfortable processing data with, say, Python or R, you'll greatly improve your data science workflow by also leveraging the power of the command line.Obtain data from websites, APIs, databases, and spreadsheetsPerform scrub operations on plain text, CSV, HTML/XML, and JSONExplore data, compute descriptive statistics, and create visualizationsManage your data science workflow using DrakeCreate reusable tools from one-liners and existing Python or R codeParallelize and distribute data-intensive pipelines using GNU ParallelModel data with dimensionality reduction, clustering, regression, and classification algorithms

    Git tasks displayed on two-page spreads provide all the context you need, without the extra fluff. Get up to speed on Git right now with Pragmatic Guide to Git. Task-oriented two-page spreads get you up and running with minimal fuss. Each left-hand page dives into the underlying implementation for each task. The right-hand page contains commands that focus on the task at hand, and cross references to other tasks that are related. You'll find what you need fast. Git is rapidly becoming the de-facto standard for the open source community. Its excellent merging capabilities, coupled with its speed and relative ease of use, make it an indispensable tool for any developer. New Git users will learn the basic tasks needed to work with Git every day, including working with remote repositories, dealing with branches and tags, exploring the history, and fixing problems when things go wrong. If you're already familiar with Git, this book will be your go-to reference for Git commands and best practices. You won't find a more practical approach to learning Git than Pragmatic Guide to Git.

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    But if one per year is good, how about Seven Languages in Seven Weeks? In this book you'll get a hands-on tour of Clojure, Haskell, Io, Prolog, Scala, Erlang, and Ruby. Whether or not your favorite language is on that list, you'll broaden your perspective of programming by examining these languages side-by-side. You'll learn something new from each, and best of all, you'll learn how to learn a language quickly. Ruby, Io, Prolog, Scala, Erlang, Clojure, Haskell. With Seven Languages in Seven Weeks, by Bruce A. Tate, you'll go beyond the syntax-and beyond the 20-minute tutorial you'll find someplace online. This book has an audacious goal: to present a meaningful exploration of seven languages within a single book. Rather than serve as a complete reference or installation guide, Seven Languages hits what's essential and unique about each language. Moreover, this approach will help teach you how to grok new languages. For each language, you'll solve a nontrivial problem, using techniques that show off the language's most important features. As the book proceeds, you'll discover the strengths and weaknesses of the languages, while dissecting the process of learning languages quickly--for example, finding the typing and programming models, decision structures, and how you interact with them. Among this group of seven, you'll explore the most critical programming models of our time. Learn the dynamic typing that makes Ruby, Python, and Perl so flexible and compelling. Understand the underlying prototype system that's at the heart of JavaScript. See how pattern matching in Prolog shaped the development of Scala and Erlang. Discover how pure functional programming in Haskell is different from the Lisp family of languages, including Clojure. Explore the concurrency techniques that are quickly becoming the backbone of a new generation of Internet applications. Find out how to use Erlang's let-it-crash philosophy for building fault-tolerant systems. Understand the actor model that drives concurrency design in Io and Scala. Learn how Clojure uses versioning to solve some of the most difficult concurrency problems. It's all here, all in one place. Use the concepts from one language to find creative solutions in another-or discover a language that may become one of your favorites.

    Currently, Lua is being used in areas ranging from embedded systems to Web development and is widely spread in the game industry, where knowledge of Lua is an indisputable asset. "Programming in Lua" is the official book about the language, giving a solid base for any programmer who wants to use Lua. Authored by Roberto Ierusalimschy, the chief architect of the language, it covers all aspects of Lua 5---from the basics to its API with C---explaining how to make good use of its features and giving numerous code examples. "Programming in Lua" is targeted at people with some programming background, but does not assume any prior knowledge about Lua or other scripting languages. This Second Edition updates the text to Lua 5.1 and brings substantial new material, including numerous new examples, a detailed explanation of the new module system, and two new chapters centered on multiple states and garbage collection.

    In this one-of-a-kind account, you'll see how the developers responsible for these flaws patched the bugs—or failed to respond at all. As you follow Klein on his journey, you'll gain deep technical knowledge and insight into how hackers approach difficult problems and experience the true joys (and frustrations) of bug hunting.Along the way you'll learn how to:Use field-tested techniques to find bugs, like identifying and tracing user input data and reverse engineering Exploit vulnerabilities like NULL pointer dereferences, buffer overflows, and type conversion flaws Develop proof of concept code that verifies the security flaw Report bugs to vendors or third party brokersA Bug Hunter's Diary is packed with real-world examples of vulnerable code and the custom programs used to find and test bugs. Whether you're hunting bugs for fun, for profit, or to make the world a safer place, you'll learn valuable new skills by looking over the shoulder of a professional bug hunter in action.

    R in a Nutshell provides a quick and practical way to learn this increasingly popular open source language and environment. You'll not only learn how to program in R, but also how to find the right user-contributed R packages for statistical modeling, visualization, and bioinformatics.The author introduces you to the R environment, including the R graphical user interface and console, and takes you through the fundamentals of the object-oriented R language. Then, through a variety of practical examples from medicine, business, and sports, you'll learn how you can use this remarkable tool to solve your own data analysis problems.Understand the basics of the language, including the nature of R objectsLearn how to write R functions and build your own packagesWork with data through visualization, statistical analysis, and other methodsExplore the wealth of packages contributed by the R communityBecome familiar with the lattice graphics package for high-level data visualizationLearn about bioinformatics packages provided by Bioconductor"I am excited about this book. R in a Nutshell is a great introduction to R, as well as a comprehensive reference for using R in data analytics and visualization. Adler provides 'real world' examples, practical advice, and scripts, making it accessible to anyone working with data, not just professional statisticians."

    Using Scala, you can write programs more concisely than in Java, as well as leverage the full power of concurrency. Since Scala runs on the JVM, it can access any Java library and is interoperable with Java frameworks. Scala for the Impatient concisely shows developers what Scala can do and how to do it. In this book, Cay Horstmann, the principal author of the international best-selling Core Java(TM), offers a rapid, code-based introduction that's completely practical. Horstmann introduces Scala concepts and techniques in "blog-sized" chunks that you can quickly master and apply. Hands-on activities guide you through well-defined stages of competency, from basic to expert. Coverage includes Getting started quickly with Scala's interpreter, syntax, tools, and unique idioms Mastering core language features: functions, arrays, maps, tuples, packages, imports, exception handling, and more Becoming familiar with object-oriented programming in Scala: classes, inheritance, and traits Using Scala for real-world programming tasks: working with files, regular expressions, and XML Working with higher-order functions and the powerful Scala collections library Leveraging Scala's powerful pattern matching and case classes Creating concurrent programs with Scala actors Implementing domain-specific languages Understanding the Scala type system Applying advanced "power tools" such as annotations, implicits, and delimited continuations Scala is rapidly reaching a tipping point that will reshape the experience of programming. This book will help object-oriented programmers build on their existing skills, allowing them to immediately construct useful applications as they gradually master advanced programming techniques.

    With it has come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book's coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting—the first comprehensive treatment of this topic in any book. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie wrote much of the statistical modeling software in S-PLUS and invented principal curves and surfaces. Tibshirani proposed the Lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, and projection pursuit.

    The Deitels' groundbreaking How to Program series offers unparalleled breadth and depth of programming concepts and intermediate-level topics for further study. The texts in the series feature hundreds of complete, working programs with thousands of lines of code--more than any other texts of their kind. Now, the world's best-selling Java textbook is again completely up-to- date with The Java 2 Platform Standard Edition (J2SE) 5.0.