This is the undisputed go-to guide to Rust, written by two members of the Rust core team, with feedback and contributions from 42 members of the community. The book assumes that you’ve written code in another programming language but makes no assumptions about which one, meaning the material is accessible and useful to developers from a wide variety of programming backgrounds.Known by the Rust community as "The Book," The Rust Programming Language includes concept chapters, where you’ll learn about a particular aspect of Rust, and project chapters, where you’ll apply what you’ve learned so far to build small programs.The Book opens with a quick hands-on project to introduce the basics then explores key concepts in depth, such as ownership, the type system, error handling, and fearless concurrency. Next come detailed explanations of Rust-oriented perspectives on topics like pattern matching, iterators, and smart pointers, with concrete examples and exercises--taking you from theory to practice.The Rust Programming Language will show you how to: Grasp important concepts unique to Rust like ownership, borrowing, and lifetimes Use Cargo, Rust’s built-in package manager, to build and maintain your code, including downloading and building dependencies Effectively use Rust’s zero-cost abstractions and employ your ownYou’ll learn to develop reliable code that’s speed and memory efficient, while avoiding the infamous and arcane programming pitfalls common at the systems level. When you need to dive down into lower-level control, this guide will show you how without taking on the customary risk of crashes or security holes and without requiring you to learn the fine points of a fickle toolchain.You’ll also learn how to create command line programs, build single- and multithreaded web servers, and much more.The Rust Programming Language fully embraces Rust’s potential to empower its users. This friendly and approachable guide will help you build not only your knowledge of Rust but also your ability to program with confidence in a wider variety of domains.

    In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

    Whether you're new to Linux or need a reliable update and reference, this is an excellent resource. Veteran bestselling author Christopher Negus provides a complete tutorial packed with major updates, revisions, and hands-on exercises so that you can confidently start using Linux today. Offers a complete restructure, complete with exercises, to make the book a better learning tool Places a strong focus on the Linux command line tools and can be used with all distributions and versions of Linux Features in-depth coverage of the tools that a power user and a Linux administrator need to get startedThis practical learning tool is ideal for anyone eager to set up a new Linux desktop system at home or curious to learn how to manage Linux server systems at work.

    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

    Consumer's identities are being stolen, and a person's every step is being tracked and stored. What once might have been dismissed as paranoia is now a hard truth, and privacy is a luxury few can afford or understand.In this explosive yet practical book, Kevin Mitnick illustrates what is happening without your knowledge--and he teaches you "the art of invisibility." Mitnick is the world's most famous--and formerly the Most Wanted--computer hacker. He has hacked into some of the country's most powerful and seemingly impenetrable agencies and companies, and at one point he was on a three-year run from the FBI. Now, though, Mitnick is reformed and is widely regarded as the expert on the subject of computer security. He knows exactly how vulnerabilities can be exploited and just what to do to prevent that from happening. In THE ART OF INVISIBILITY Mitnick provides both online and real life tactics and inexpensive methods to protect you and your family, in easy step-by-step instructions. He even talks about more advanced "elite" techniques, which, if used properly, can maximize your privacy. Invisibility isn't just for superheroes--privacy is a power you deserve and need in this modern age.

    Theory and practice in the design of data graphics, 250 illustrations of the best (and a few of the worst) statistical graphics, with detailed analysis of how to display data for precise, effective, quick analysis. Design of the high-resolution displays, small multiples. Editing and improving graphics. The data-ink ratio. Time-series, relational graphics, data maps, multivariate designs. Detection of graphical deception: design variation vs. data variation. Sources of deception. Aesthetics and data graphical displays. This is the second edition of The Visual Display of Quantitative Information. Recently published, this new edition provides excellent color reproductions of the many graphics of William Playfair, adds color to other images, and includes all the changes and corrections accumulated during 17 printings of the first edition.

    A pocket-sized overview of roles, artifacts and the sprint cycle, adapted from the bestseller The Elements of Scrum by Chris Sims & Hillary Louise Johnson

    You’ll learn everything from the basics of database integration and the use of JavaScript to browser-automation tools like Selenium, and advanced topics such as NoSQL, Web Sockets, and async programming.Ideal for beginners, this book teaches a development methodology that leads to peace of mind, cleaner code, and better web apps.

    Fueled by significant benefits and an impressive portfolio of real-world applications already in production, Rails is destined to continue making significant inroads in coming years.Each new Rails application showing up on the web adds yet more to the collective wisdom of the Rails development community. Yesterday's best practices yield to today's latest and greatest techniques, as the state of the art is continually refined in kitchens all across the Internet. Indeed, these are times of great progress.At the same time, it's easy to get left behind in the wake of progress. Advanced Rails Recipes keeps you on the cutting edge of Rails development and, more importantly, continues to turn this fast-paced framework to your advantage.Advanced Rails Recipes is filled with pragmatic recipes you'll use on every Rails project. And by taking the code in these recipes and slipping it into your application you'll not only deliver your application quicker, you'll do so with the confidence that it's done right.The book includes contributions from Aaron Batalion, Adam Keys, Adam Wiggins, Andre Lewis, Andrew Kappen, Benjamin Curtis, Ben Smith, Chris Bernard, Chris Haupt, Chris Wanstrath, Cody Fauser, Dan Benjamin, Dan Manges, Daniel Fischer, David Bock, David Chelimsky, David Heinemeier Hansson, Erik Hatcher, Ezra Zygmuntowicz, Geoffrey Grosenbach, Giles Bowkett, Greg Hansen, Gregg Pollack, Hemant Kumar, Hugh Bien, Jamie Orchard-Hays, Jamis Buck, Jared Haworth, Jarkko Laine, Jason LaPier, Jay Fields, John Dewey, Jonathan Dahl, Josep Blanquer, Josh Stephenson, Josh Susser, Kevin Clark, Luke Francl, Mark Bates, Marty Haught, Matthew Bass, Michael Slater, Mike Clark, Mike Hagedorn, Mike Mangino, Mike Naberezny, Mike Subelsky, Nathaniel Talbott, PJ Hyett, Patrick Reagan, Peter Marklund, Pierre-Alexandre Meyer, Rick Olson, Ryan Bates, Scott Barron, Tony Primerano, Val Aleksenko, and Warren Konkel.

    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.

    If you're new to Elixir, its functional style can seem difficult, but with help from this hands-on introduction, you'll scale the learning curve and discover how enjoyable, powerful, and fun this language can be. Elixir combines the robust functional programming of Erlang with an approach that looks more like Ruby and reaches toward metaprogramming with powerful macro features.Authors Simon St. Laurent and J. David Eisenberg show you how to write simple Elixir programs by teaching you one skill at a time. You’ll learn about pattern matching, recursion, message passing, process-oriented programming, and establishing pathways for data rather than telling it where to go. By the end of your journey, you’ll understand why Elixir is ideal for concurrency and resilience.* Get comfortable with IEx, Elixir's command line interface* Become familiar with Elixir’s basic structures by working with numbers* Discover atoms, pattern matching, and guards: the foundations of your program structure* Delve into the heart of Elixir processing with recursion, strings, lists, and higher-order functions* Create processes, send messages among them, and apply pattern matching to incoming messages* Store and manipulate structured data with Erlang Term * Storage (ETS) and the Mnesia database* Build resilient applications with the Open Telecom Platform (OTP)* Define macros with Elixir's meta-programming tools.

    Getting Started with AWS provides an introduction to Amazon Web Services, examples of what you can do with AWS, basic information that you need to know to get started, and links to resources and documentation that will help you learn more no matter what your use case is.

    Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms.Inside, you’ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works.Topics include:Data Structures and AlgorithmsStrings and TextNumbers, Dates, and TimesIterators and GeneratorsFiles and I/OData Encoding and ProcessingFunctionsClasses and ObjectsMetaprogrammingModules and PackagesNetwork and Web ProgrammingConcurrencyUtility Scripting and System AdministrationTesting, Debugging, and ExceptionsC Extensions