In "The Definitive Guide to Django: Web Development Done Right," Adrian Holovaty, one of Django's creators, and Django lead developer Jacob KaplanMoss show you how they use this framework to create awardwinning web sites. Over the course of three parts, they guide you through the creation of a web application reminiscent of chicagocrime.org.The first part of the book introduces Django fundamentals like installation and configuration. You'll learn about creating the components that power a Django-driven web site. The second part delves into the more sophisticated features of Django, like outputting nonHTML content (such as RSS feeds and PDFs), plus caching and user management. The third part serves as a detailed reference to Django's many configuration options and commands. The book even includes seven appendices for looking up configurations options and commands. In all, this book provides the ultimate tutorial and reference to the popular Django framework. What you'll learnThe first half of this book explains in-depth how to build web applications using Django including the basics of dynamic web pages, the Django templating system interacting with databases, and web forms. The second half of this book discusses higher-level concepts such as caching, security, and how to deploy Django. The appendices form a reference for the commands and configurations available in Django. Who this book is forAnyone who wants to use the powerful Django framework to build dynamic web sites quickly and easily! "

    Are You Ready To Learn Python Easily? Learning Python Programming in 7 days is possible, although it might not look like it

    Written by three prominent members of the Perl community who each have several years of experience teaching Perl around the world, this edition has been updated to account for all the recent changes to the language up to Perl 5.8.Perl is the language for people who want to get work done. It started as a tool for Unix system administrators who needed something powerful for small tasks. Since then, Perl has blossomed into a full-featured programming language used for web programming, database manipulation, XML processing, and system administration--on practically all platforms--while remaining the favorite tool for the small daily tasks it was designed for. You might start using Perl because you need it, but you'll continue to use it because you love it.Informed by their years of success at teaching Perl as consultants, the authors have re-engineered the Llama to better match the pace and scope appropriate for readers getting started with Perl, while retaining the detailed discussion, thorough examples, and eclectic wit for which the Llama is famous.The book includes new exercises and solutions so you can practice what you've learned while it's still fresh in your mind. Here are just some of the topics covered:Perl variable typessubroutinesfile operationsregular expressionstext processingstrings and sortingprocess managementusing third party modulesIf you ask Perl programmers today what book they relied on most when they were learning Perl, you'll find that an overwhelming majority will point to the Llama. With good reason. Other books may teach you to program in Perl, but this book will turn you into a Perl programmer.

    Even experienced JavaScripters sometimes find themselves overwhelmed as complex apps grow into a tangled web of callbacks.With Async JavaScript, you'll learn about:Event schedulingThe PubSub patternPromises and Deferred objectsFlow control with Async.jsRecipes for common async scenariosMulti-threading with Web WorkersAltJS languagesand more, with examples tailored to jQuery and Node.js.

    Learn critical lessons from a person who helped design and build one of the largest high-performance .NET systems in the world.This book does not just teach you how the CLR works—it teaches you exactly what you need to do now to obtain the best performance today. It will expertly guide you through the nuts and bolts of extreme performance optimization in .NET, complete with in-depth examinations of CLR functionality, free tool recommendations and tutorials, useful anecdotes, and step-by-step guides to measure and improve performance.Among the topics you will learn are how to:-Choose what to measure and why-Use many amazing tools, freely available, to solve problems quickly-Understand the .NET garbage collector and its effect on your application-Use effective coding patterns that lead to optimal garbage collection performance-Diagnose common GC-related issues-Reduce costs of JITting-Use multiple threads sanely and effectively, avoiding synchronization problems-Know which .NET features and APIs to use and which to avoid-Use code generation to avoid performance problems-Measure everything and expose hidden performance issues-Instrument your program with performance counters and ETW events-Use the latest and greatest .NET features-Ensure your code can run on mobile devices without problems-Build a performance-minded team…and much more.

    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

    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.

    By presenting the emerging best practices and designs from the Scala community, it guides you through dozens of powerful techniques example by example.About the BookScala is a powerful JVM language that blends the functional and OO programming models. You'll have no trouble getting introductions to Scala in books or online, but it's hard to find great examples and insights from experienced practitioners. You'll find them in Scala in Depth.There's little heavy-handed theory here—just dozens of crisp, practical techniques for coding in Scala. Written for readers who know Java, Scala, or another OO language.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.What's InsideConcise, expressive, and readable code style How to integrate Scala into your existing Java projects Scala's 2.8.0 collections API How to use actors for concurrent programming Mastering the Scala type system Scala's OO features—type member inheritance, multiple inheritance, and composition Functional concepts and patterns—immutability, applicative functors, and monads========================================​==========Table of ContentsScala—a blended language The core rules Modicum of style—coding conventions Utilizing object orientation Using implicits to write expressive code The type system Using implicits and types together Using the right collection Actors Integrating Scala with Java Patterns in functional programming

    But can you also build web sites that are usable by machines? That's where the future lies, and that's what RESTful Web Services shows you how to do. The World Wide Web is the most popular distributed application in history, and Web services and mashups have turned it into a powerful distributed computing platform. But today's web service technologies have lost sight of the simplicity that made the Web successful. They don't work like the Web, and they're missing out on its advantages. This book puts the "Web" back into web services. It shows how you can connect to the programmable web with the technologies you already use every day. The key is REST, the architectural style that drives the Web. This book:Emphasizes the power of basic Web technologies -- the HTTP application protocol, the URI naming standard, and the XML markup language Introduces the Resource-Oriented Architecture (ROA), a common-sense set of rules for designing RESTful web services Shows how a RESTful design is simpler, more versatile, and more scalable than a design based on Remote Procedure Calls (RPC) Includes real-world examples of RESTful web services, like Amazon's Simple Storage Service and the Atom Publishing Protocol Discusses web service clients for popular programming languages Shows how to implement RESTful services in three popular frameworks -- Ruby on Rails, Restlet (for Java), and Django (for Python) Focuses on practical issues: how to design and implement RESTful web services and clients This is the first book that applies the REST design philosophy to real web services. It sets down the best practices you need to make your design a success, and the techniques you need to turn your design into working code. You can harness the power of the Web for programmable applications: you just have to work with the Web instead of against it. This book shows you how.

    

    The concepts and techniques described are the actual ones used by real game studios like Electronic Arts and Naughty Dog. The examples are often grounded in specific technologies, but the discussion extends way beyond any particular engine or API. The references and citations make it a great jumping off point for those who wish to dig deeper into any particular aspect of the game development process.Intended as the text for a college level series in game programming, this book can also be used by amateur software engineers, hobbyists, self-taught game programmers, and existing members of the game industry. Junior game engineers can use it to solidify their understanding of game technology and engine architecture. Even senior engineers who specialize in one particular field of game development can benefit from the bigger picture presented in these pages.

    Packed with examples and helpful recommendations, the book has helped everyone--from novices to experienced developers, and from Oracle Forms developers to database administrators--make the most of PL/SQL. The fourth edition is a comprehensive update, adding significant new content and extending coverage to include the very latest Oracle version, Oracle Database 10g Release 2. It describes such new features as the PL/SQL optimizing compiler, conditional compilation, compile-time warnings, regular expressions, set operators for nested tables, nonsequential collections in FORALL, the programmer-defined quoting mechanism, the ability to backtrace an exception to a line number, a variety of new built-in packages, and support for IEEE 754 compliant floating-point numbers. The new edition adds brand-new chapters on security (including encryption, row-level security, fine-grained auditing, and application contexts), file, email, and web I/O (including the built-in packages DBMS_OUTPUT, UTL_FILE, UTL_MAIL, UTL_SMTP, and UTL_HTTP) and globalization and localization. Co-authored by the world's foremost PL/SQL authority, Steven Feuerstein, this classic reference provides language syntax, best practices, and extensive code, ranging from simple examples to complete applications--making it a must-have on your road to PL/SQL mastery. A companion web site contains many more examples and additional technical content for enhanced learning.

    Major retailers are predicting everything from when their customers are pregnant to when they want a new pair of Chuck Taylors. It's a brave new world where seemingly meaningless data can be transformed into valuable insight to drive smart business decisions.But how does one exactly do data science? Do you have to hire one of these priests of the dark arts, the "data scientist," to extract this gold from your data? Nope.Data science is little more than using straight-forward steps to process raw data into actionable insight. And in Data Smart, author and data scientist John Foreman will show you how that's done within the familiar environment of a spreadsheet. Why a spreadsheet? It's comfortable! You get to look at the data every step of the way, building confidence as you learn the tricks of the trade. Plus, spreadsheets are a vendor-neutral place to learn data science without the hype. But don't let the Excel sheets fool you. This is a book for those serious about learning the analytic techniques, the math and the magic, behind big data.Each chapter will cover a different technique in a spreadsheet so you can follow along: - Mathematical optimization, including non-linear programming and genetic algorithms- Clustering via k-means, spherical k-means, and graph modularity- Data mining in graphs, such as outlier detection- Supervised AI through logistic regression, ensemble models, and bag-of-words models- Forecasting, seasonal adjustments, and prediction intervals through monte carlo simulation- Moving from spreadsheets into the R programming languageYou get your hands dirty as you work alongside John through each technique. But never fear, the topics are readily applicable and the author laces humor throughout. You'll even learn what a dead squirrel has to do with optimization modeling, which you no doubt are dying to know.

    It is the technology behind photo tagging systems at Facebook and Google, self-driving cars, speech recognition systems on your smartphone, and much more.In particular, Deep learning excels at solving machine perception problems: understanding the content of image data, video data, or sound data. Here's a simple example: say you have a large collection of images, and that you want tags associated with each image, for example, "dog," "cat," etc. Deep learning can allow you to create a system that understands how to map such tags to images, learning only from examples. This system can then be applied to new images, automating the task of photo tagging. A deep learning model only has to be fed examples of a task to start generating useful results on new data.

    Legendary testing expert James Whittaker, until recently a Google testing leader, and two top Google experts reveal exactly how Google tests software, offering brand-new best practices you can use even if you're not quite Google's size...yet! Breakthrough Techniques You Can Actually Use Discover 100% practical, amazingly scalable techniques for analyzing risk and planning tests...thinking like real users...implementing exploratory, black box, white box, and acceptance testing...getting usable feedback...tracking issues...choosing and creating tools...testing "Docs & Mocks," interfaces, classes, modules, libraries, binaries, services, and infrastructure...reviewing code and refactoring...using test hooks, presubmit scripts, queues, continuous builds, and more. With these techniques, you can transform testing from a bottleneck into an accelerator-and make your whole organization more productive!