Verification that algorithms work is emphasized more than their complexity. An effective use of examples, and huge number of interesting exercises, demonstrate the topics of trees and distance, matchings and factors, connectivity and paths, graph coloring, edges and cycles, and planar graphs. For those who need to learn to make coherent arguments in the fields of mathematics and computer science.

    See the website for links to the C++ and Java version.Have you ever...Wanted to work at an exciting futuristic company?Struggled with an interview problem thatcould have been solved in 15 minutes?Wished you could study real-world computing problems?If so, you need to read Elements of Programming Interviews (EPI).EPI is your comprehensive guide to interviewing for software development roles.The core of EPI is a collection of over 250 problems with detailed solutions. The problems are representative of interview questions asked at leading software companies. The problems are illustrated with 200 figures, 300 tested programs, and 150 additional variants.The book begins with a summary of the nontechnical aspects of interviewing, such as strategies for a great interview, common mistakes, perspectives from the other side of the table, tips on negotiating the best offer, and a guide to the best ways to use EPI. We also provide a summary of data structures, algorithms, and problem solving patterns.Coding problems are presented through a series of chapters on basic and advanced data structures, searching, sorting, algorithm design principles, and concurrency. Each chapter stars with a brief introduction, a case study, top tips, and a review of the most important library methods. This is followed by a broad and thought-provoking set of problems.A practical, fun approach to computer science fundamentals, as seen through the lens of common programming interview questions. Jeff Atwood/Co-founder, Stack Overflow and Discourse

    The focus is on algorithms and hence the book is well suited for students in computer science and engineering. Motivation is provided from the application areas: all solutions and techniques from computational geometry are related to particular applications in robotics, graphics, CAD/CAM, and geographic information systems. For students this motivation will be especially welcome. Modern insights in computational geometry are used to provide solutions that are both efficient and easy to understand and implement. All the basic techniques and topics from computational geometry, as well as several more advanced topics, are covered. The book is largely self-contained and can be used for self-study by anyone with a basic background in algorithms. In the second edition, besides revisions to the first edition, a number of new exercises have been added.

    “Big data” refers to our burgeoning ability to crunch vast collections of information, analyze it instantly, and draw sometimes profoundly surprising conclusions from it. This emerging science can translate myriad phenomena—from the price of airline tickets to the text of millions of books—into searchable form, and uses our increasing computing power to unearth epiphanies that we never could have seen before. A revolution on par with the Internet or perhaps even the printing press, big data will change the way we think about business, health, politics, education, and innovation in the years to come. It also poses fresh threats, from the inevitable end of privacy as we know it to the prospect of being penalized for things we haven’t even done yet, based on big data’s ability to predict our future behavior.In this brilliantly clear, often surprising work, two leading experts explain what big data is, how it will change our lives, and what we can do to protect ourselves from its hazards. Big Data is the first big book about the next big thing.www.big-data-book.com

    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.

    The pytest testing framework helps you write tests quickly and keep them readable and maintainable - with no boilerplate code. Using a robust yet simple fixture model, it's just as easy to write small tests with pytest as it is to scale up to complex functional testing for applications, packages, and libraries. This book shows you how.For Python-based projects, pytest is the undeniable choice to test your code if you're looking for a full-featured, API-independent, flexible, and extensible testing framework. With a full-bodied fixture model that is unmatched in any other tool, the pytest framework gives you powerful features such as assert rewriting and plug-in capability - with no boilerplate code.With simple step-by-step instructions and sample code, this book gets you up to speed quickly on this easy-to-learn and robust tool. Write short, maintainable tests that elegantly express what you're testing. Add powerful testing features and still speed up test times by distributing tests across multiple processors and running tests in parallel. Use the built-in assert statements to reduce false test failures by separating setup and test failures. Test error conditions and corner cases with expected exception testing, and use one test to run many test cases with parameterized testing. Extend pytest with plugins, connect it to continuous integration systems, and use it in tandem with tox, mock, coverage, unittest, and doctest.Write simple, maintainable tests that elegantly express what you're testing and why.What You Need: The examples in this book are written using Python 3.6 and pytest 3.0. However, pytest 3.0 supports Python 2.6, 2.7, and Python 3.3-3.6.

    But what if you could have your computer do them for you?In "Automate the Boring Stuff with Python," you'll learn how to use Python to write programs that do in minutes what would take you hours to do by hand no prior programming experience required. Once you've mastered the basics of programming, you'll create Python programs that effortlessly perform useful and impressive feats of automation to: Search for text in a file or across multiple filesCreate, update, move, and rename files and foldersSearch the Web and download online contentUpdate and format data in Excel spreadsheets of any sizeSplit, merge, watermark, and encrypt PDFsSend reminder emails and text notificationsFill out online formsStep-by-step instructions walk you through each program, and practice projects at the end of each chapter challenge you to improve those programs and use your newfound skills to automate similar tasks.Don't spend your time doing work a well-trained monkey could do. Even if you've never written a line of code, you can make your computer do the grunt work. Learn how in "Automate the Boring Stuff with Python.""

    With this practical guide, you’ll learn how to use Python scripts and web APIs to gather and process data from thousands—or even millions—of web pages at once. Ideal for programmers, security professionals, and web administrators familiar with Python, this book not only teaches basic web scraping mechanics, but also delves into more advanced topics, such as analyzing raw data or using scrapers for frontend website testing. Code samples are available to help you understand the concepts in practice. Learn how to parse complicated HTML pages Traverse multiple pages and sites Get a general overview of APIs and how they work Learn several methods for storing the data you scrape Download, read, and extract data from documents Use tools and techniques to clean badly formatted data Read and write natural languages Crawl through forms and logins Understand how to scrape JavaScript Learn image processing and text recognition

    It also covers MySQL, and PostgreSQL. It contains examples which have been tested against each SQL platform, with incompatibilities or platform distinctives called out and explained.

    We are living in an age where data comes in abundance, and thanks to the self-learning algorithms from the field of machine learning, we can turn this data into knowledge. Automated speech recognition on our smart phones, web search engines, e-mail spam filters, the recommendation systems of our favorite movie streaming services – machine learning makes it all possible.Thanks to the many powerful open-source libraries that have been developed in recent years, machine learning is now right at our fingertips. Python provides the perfect environment to build machine learning systems productively.This book will teach you the fundamentals of machine learning and how to utilize these in real-world applications using Python. Step-by-step, you will expand your skill set with the best practices for transforming raw data into useful information, developing learning algorithms efficiently, and evaluating results.You will discover the different problem categories that machine learning can solve and explore how to classify objects, predict continuous outcomes with regression analysis, and find hidden structures in data via clustering. You will build your own machine learning system for sentiment analysis and finally, learn how to embed your model into a web app to share with the world

    Windows Presentation Foundation (WPF) is the recommended technology for creating Windows user interfaces, giving you the power to create richer and more compelling applications than you dreamed possible. Whether you want to develop traditional user interfaces or integrate 3D graphics, audio/video, animation, dynamic skinning, multi-touch, rich document support, speech recognition, or more, WPF enables you to do so in a seamless, resolution-independent manner. WPF 4 Unleashed is the authoritative book that covers it all, in a practical and approachable fashion, authored by WPF guru and Microsoft developer Adam Nathan. Covers everything you need to know about Extensible Application Markup Language (XAML) Examines the WPF feature areas in incredible depth: controls, layout, resources, data binding, styling, graphics, animation, and more Highlights the latest features, such as multi-touch, text rendering improvements, XAML language enhancements, new controls, the Visual State Manager, easing functions, and much more Delves into topics that aren't covered by most books: 3D, speech, audio/video, documents, effects Shows how to create popular UI elements, such as Galleries, ScreenTips, and more Demonstrates how to create sophisticated UI mechanisms, such as Visual Studio-like collapsible/dockable panes Explains how to create first-class custom controls for WPF Demonstrates how to create hybrid WPF software that leverages Windows Forms, DirectX, ActiveX, or other non-WPF technologies Explains how to exploit new Windows 7 features, such as Jump Lists and taskbar customizations

    Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning.The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models.Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

    You'll learn how to create responsive, data-driven websites with PHP, MySQL, and JavaScript, regardless of whether you already know how to program. Discover how the powerful combination of PHP and MySQL provides an easy way to build modern websites complete with dynamic data and user interaction. You'll also learn how to add JavaScript to create rich Internet applications and websites.Learning PHP, MySQL, and JavaScript explains each technology separately, shows you how to combine them, and introduces valuable web programming concepts, including objects, XHTML, cookies, and session management. You'll practice what you've learned with review questions in each chapter, and find a sample social networking platform built with the elements introduced in this book. This book will help you:-Understand PHP essentials and the basics of object-oriented programming-Master MySQL, from database structure to complex queries-Create web pages with PHP and MySQL by integrating forms and other HTML features-Learn about JavaScript, from functions and event handling to accessing the Document Object Model-Use libraries and packages, including the Smarty web template system, PEAR program repository, and the Yahoo! User Interface Library -Make Ajax calls and turn your website into a highly dynamic environment-Upload and manipulate files and images, validate user input, and secure your applications

    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.

    No longer is execution speed the sole criterion for judging compiled code. Today, code might be judged on how small it is, how much power it consumes, how well it compresses, or how many page faults it generates. In this evolving environment, the task of building a successful compiler relies upon the compiler writer's ability to balance and blend algorithms, engineering insights, and careful planning. Today's compiler writer must choose a path through a design space that is filled with diverse alternatives, each with distinct costs, advantages, and complexities.Engineering a Compiler explores this design space by presenting some of the ways these problems have been solved, and the constraints that made each of those solutions attractive. By understanding the parameters of the problem and their impact on compiler design, the authors hope to convey both the depth of the problems and the breadth of possible solutions. Their goal is to cover a broad enough selection of material to show readers that real tradeoffs exist, and that the impact of those choices can be both subtle and far-reaching.Authors Keith Cooper and Linda Torczon convey both the art and the science of compiler construction and show best practice algorithms for the major passes of a compiler. Their text re-balances the curriculum for an introductory course in compiler construction to reflect the issues that arise in current practice.