You will be able to look over the shoulder of major coding and design experts to see problems through their eyes.This is not simply another design patterns book, or another software engineering treatise on the right and wrong way to do things. The authors think aloud as they work through their project's architecture, the tradeoffs made in its construction, and when it was important to break rules. Beautiful Code is an opportunity for master coders to tell their story. All author royalties will be donated to Amnesty International.

    This updated edition includes all the changes in Python 3, itself a significant shift from earlier versions of Python.The book begins with basic but useful programs that teach the core features of syntax, control flow, and data structures. It then moves to larger applications involving code management, object-oriented programming, web development, and converting code from earlier versions of Python.True to his audience of experienced developers, the author covers common programming language features concisely, while giving more detail to those features unique to Python.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.

    As John invested in these skills his career took off, and he became a highly paid, highly sought-after developer and consultant. Today John helps more than 1.4 million programmers every year to increase their income by developing this unique blend of skills. "If you're a developer, green or a veteran, you owe it to yourself to read The Complete Software Developers Career Guide." - Jason Down, Platform Developer, Ontario, Canada What You Will Learn in This Book How to systematically find and fill the gaps in your technical knowledge so you can face any new challenge with confidence Should you take contract work - or hold out for a salaried position? Which will earn you more, what the tradeoffs are, and how your personality should sway your choice Should you learn JavaScript, C#, Python, C++? How to decide which programming language you should master first Ever notice how every job ever posted requires "3-5 years of experience," which you don't have? Simple solution for this frustrating chicken-and-egg problem that allows you to build legitimate job experience while you learn to code Is earning a computer science degree a necessity - or a total waste of time? How to get a college degree with maximum credibility and minimum debt Coding bootcampssome are great, some are complete scams. How to tell the difference so you don't find yourself cheated out of $10,000 Interviewer tells you, "Dress code is casual around here - the development team wears flipflops." What should you wear? How do you deal with a boss who's a micromanager. Plus how helping your manager with his goals can make you the MVP of your team The technical skills that every professional developer must have - but no one teaches you (most developers are missing some critical pieces, they don't teach this stuff in college, you're expected to just "know" this) An inside look at the recruiting industry. What that "friendly" recruiter really wants from you, how they get paid, and how to avoid getting pigeonholed into a job you'll hate Who Should Read This Book Entry-Level Developers This book will show you how to ensure you have the technical skills your future boss is looking for, create a resume that leaps off a hiring manager's desk, and escape the "no work experience" trap. Mid-Career Developers You'll see how to find and fill in gaps in your technical knowledge, position yourself as the one team member your boss can't live without, and turn those dreaded annual reviews into chance to make an iron-clad case for your salary bump. Senior Developers This book will show you how to become a specialist who can command above-market wages, how building a name for yourself can make opportunities come to you, and how to decide whether consulting or entrepreneurship are paths you should pursue.

    Commercial game development expert Robert Nystrom presents an array of general solutions to problems encountered in game development. For example, you'll learn how double-buffering enables a player to perceive smooth and realistic motion, and how the service locator pattern can help you provide access to services such as sound without coupling your code to any particular sound driver or sound hardware. Games have much in common with other software, but also a number of unique constraints. Some of the patterns in this book are well-known in other domains of software development. Other of the patterns are unique to gaming. In either case, Robert Nystrom bridges from the ivory tower world of software architecture to the in-the-trenches reality of hardcore game programming. You'll learn the patterns and the general problems that they solve. You'll come away able to apply powerful and reusable architectural solutions that enable you to produce higher quality games with less effort than before. Applies classic design patterns to game programming. Introduces new patterns specific to game programming. Brings abstract software architecture down to Earth with approachable writing and an emphasis on simple code that shows each pattern in practice. What you'll learn Overcome architectural challenges unique to game programming Apply lessons from the larger software world to games. Tie different parts of a game (graphics, sound, AI) into a cohesive whole. Create elegant and maintainable architecture. Achieve good, low-level performance. Gain insight into professional, game development. Who this book is forGame Programming Patterns is aimed at professional game programmers who, while successful in shipping games, are frustrated at how hard it sometimes is to add and modify features when a game is under development. Game Programming Patterns shows how to apply modern software practices to the problem of game development while still maintaining the blazing-fast performance demanded by hard-core gamers. Game Programming Patterns also appeals to those learning about game programming in their spare time. Hobbyists and aspiring professionals alike will find much to learn in this book about pathfinding, collision detection, and other game-programming problem domains.

    No statistical knowledge is required, and your programming skills can range from hobbyist to pro.Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to: Create artful graphs to visualize complex data sets and functions Write more efficient code using parallel R and vectorization Interface R with C/C++ and Python for increased speed or functionality Find new R packages for text analysis, image manipulation, and more Squash annoying bugs with advanced debugging techniques Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.

    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

    Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and are natural extensions and consequences of previous concepts. This book can be used for readers who have a solid mathematics background. It can also be used in a way that stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures for a variety of situations, and less concerned with formal optimality investigations.

    Deciding whether to build another power generation plant in the next five years requires forecasts of future demand. Scheduling staff in a call centre next week requires forecasts of call volumes. Stocking an inventory requires forecasts of stock requirements. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly. Examples use R with many data sets taken from the authors' own consulting experience.

    It has been winning converts from dynamic language enthusiasts as well as users of traditional compiled languages. The former appreciate the robustness and efficiency that Go's lightweight type system brings to their code; the latter find Go's simplicity and fast tools a refreshing change. Thanks to its well-designed standard libraries and its excellent support for concurrent programming, Go is fast becoming the language of choice for distributed systems. The Go Programming Language is the definitive book on Go for the working programmer. It assumes no prior knowledge of Go, nor any other specific programming language, so you'll find it an accessible guide whether you come from JavaScript, Ruby, Python, Java, or C++. The book will quickly get you started using Go effectively from the beginning, and by the end, you will know how to use it well to write clear, idiomatic and efficient programs to solve real-world problems. You'll understand not just how to use its standard libraries, but how they work, and how to apply the same design techniques to your own projects. The earlier chapters will introduce you to the basic concepts of Go programming---numbers, strings, functions---while at the same time presenting important computer science concepts like recursion, and useful examples of graphics, UTF-8, and error handling. The chapters on methods and interfaces will show you a new way to think about object-oriented programming; the chapter on concurrency explains why concurrency is so important in modern programming, and how Go helps you handle it well. You'll also learn about Go's pragmatic but effective approach to testing; how to build, test, and manage projects using the go tool, and the art of metaprogramming using reflection. The book contains hundreds of interesting and practical examples that cover the whole language and a wide range of applications. The code samples from the book are available for download from gopl.io.

    A comprehensive introduction to the subject, this book shows in detail how such problems can be solved numerically with great efficiency. The focus is on recognizing convex optimization problems and then finding the most appropriate technique for solving them. The text contains many worked examples and homework exercises and will appeal to students, researchers and practitioners in fields such as engineering, computer science, mathematics, statistics, finance, and economics.

    The Productive Programmer offers critical timesaving and productivity tools that you can adopt right away, no matter what platform you use. Master developer Neal Ford not only offers advice on the mechanics of productivity-how to work smarter, spurn interruptions, get the most out your computer, and avoid repetition-he also details valuable practices that will help you elude common traps, improve your code, and become more valuable to your team. You'll learn to:Write the test before you write the codeManage the lifecycle of your objects fastidiously Build only what you need now, not what you might need later Apply ancient philosophies to software development Question authority, rather than blindly adhere to standardsMake hard things easier and impossible things possible through meta-programming Be sure all code within a method is at the same level of abstraction Pick the right editor and assemble the best tools for the job This isn't theory, but the fruits of Ford's real-world experience as an Application Architect at the global IT consultancy ThoughtWorks. Whether you're a beginner or a pro with years of experience, you'll improve your work and your career with the simple and straightforward principles in The Productive Programmer.

    How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates. Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. You’ll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning. Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell Leverage Spark’s powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlib Use one programming paradigm instead of mixing and matching tools like Hive, Hadoop, Mahout, and Storm Learn how to deploy interactive, batch, and streaming applications Connect to data sources including HDFS, Hive, JSON, and S3 Master advanced topics like data partitioning and shared variables

    'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating journey through the revolution in data analysis following the introduction of electronic computation in the 1950s. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic regression, empirical Bayes, the jackknife and bootstrap, random forests, neural networks, Markov chain Monte Carlo, inference after model selection, and dozens more. The distinctly modern approach integrates methodology and algorithms with statistical inference. The book ends with speculation on the future direction of statistics and data science.

    Some books try to give you copy-and-paste instructions for how to deal with every single system issue that may arise, but How Linux Works actually shows you how the Linux system functions so that you can come up with your own solutions. After a guided tour of filesystems, the boot sequence, system management basics, and networking, author Brian Ward delves into open-ended topics such as development tools, custom kernels, and buying hardware, all from an administrator's point of view. With a mixture of background theory and real-world examples, this book shows both "how" to administer Linux, and "why" each particular technique works, so that you will know how to make Linux work for you.

    Now this same team provides the best explanation yet of these new features, and of concurrency in general. Concurrency is no longer a subject for advanced users only. Every Java developer should read this book."--Martin BuchholzJDK Concurrency Czar, Sun Microsystems"For the past 30 years, computer performance has been driven by Moore's Law; from now on, it will be driven by Amdahl's Law. Writing code that effectively exploits multiple processors can be very challenging. Java Concurrency in Practice provides you with the concepts and techniques needed to write safe and scalable Java programs for today's--and tomorrow's--systems."--Doron RajwanResearch Scientist, Intel Corp"This is the book you need if you're writing--or designing, or debugging, or maintaining, or contemplating--multithreaded Java programs. If you've ever had to synchronize a method and you weren't sure why, you owe it to yourself and your users to read this book, cover to cover."--Ted NewardAuthor of Effective Enterprise Java"Brian addresses the fundamental issues and complexities of concurrency with uncommon clarity. This book is a must-read for anyone who uses threads and cares about performance."--Kirk PepperdineCTO, JavaPerformanceTuning.com"This book covers a very deep and subtle topic in a very clear and concise way, making it the perfect Java Concurrency reference manual. Each page is filled with the problems (and solutions!) that programmers struggle with every day. Effectively exploiting concurrency is becoming more and more important now that Moore's Law is delivering more cores but not faster cores, and this book will show you how to do it."--Dr. Cliff ClickSenior Software Engineer, Azul Systems"I have a strong interest in concurrency, and have probably written more thread deadlocks and made more synchronization mistakes than most programmers. Brian's book is the most readable on the topic of threading and concurrency in Java, and deals with this difficult subject with a wonderful hands-on approach. This is a book I am recommending to all my readers of The Java Specialists' Newsletter, because it is interesting, useful, and relevant to the problems facing Java developers today."--Dr. Heinz KabutzThe Java Specialists' Newsletter"I've focused a career on simplifying simple problems, but this book ambitiously and effectively works to simplify a complex but critical subject: concurrency. Java Concurrency in Practice is revolutionary in its approach, smooth and easy in style, and timely in its delivery--it's destined to be a very important book."--Bruce TateAuthor of Beyond Java" Java Concurrency in Practice is an invaluable compilation of threading know-how for Java developers. I found reading this book intellectually exciting, in part because it is an excellent introduction to Java's concurrency API, but mostly because it captures in a thorough and accessible way expert knowledge on threading not easily found elsewhere."--Bill VennersAuthor of Inside the Java Virtual MachineThreads are a fundamental part of the Java platform. As multicore processors become the norm, using concurrency effectively becomes essential for building high-performance applications. Java SE 5 and 6 are a huge step forward for the development of concurrent applications, with improvements to the Java Virtual Machine to support high-performance, highly scalable concurrent classes and a rich set of new concurrency building blocks. In Java Concurrency in Practice , the creators of these new facilities explain not only how they work and how to use them, but also the motivation and design patterns behind them.However, developing, testing, and debugging multithreaded programs can still be very difficult; it is all too easy to create concurrent programs that appear to work, but fail when it matters most: in production, under heavy load. Java Concurrency in Practice arms readers with both the theoretical underpinnings and concrete techniques for building reliable, scalable, maintainable concurrent applications. Rather than simply offering an inventory of concurrency APIs and mechanisms, it provides design rules, patterns, and mental models that make it easier to build concurrent programs that are both correct and performant.This book covers:Basic concepts of concurrency and thread safety Techniques for building and composing thread-safe classes Using the concurrency building blocks in java.util.concurrent Performance optimization dos and don'ts Testing concurrent programs Advanced topics such as atomic variables, nonblocking algorithms, and the Java Memory Model