It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of "data science" for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (or MOOC) offered by the pioneering MIT--Harvard collaboration edX.Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. The book does not require knowledge of mathematics beyond high school algebra, but does assume that readers are comfortable with rigorous thinking and not intimidated by mathematical concepts. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming.Introduction to Computation and Programming Using Python can serve as a stepping-stone to more advanced computer science courses, or as a basic grounding in computational problem solving for students in other disciplines.

    But while most of us today can work a computer--albeit with the help of the ever-present computer software manual--we know little about what goes on inside the box and virtually nothing about software designor the world of computer programming. In Patterns of Software, the respected software pioneer and computer scientist, Richard Gabriel, gives us an informative inside look at the world of software design and computer programming and the business that surrounds them. In this wide-ranging volume, Gabriel discusses such topics as whatmakes a successful programming language, how the rest of the world looks at and responds to the work of computer scientists, how he first became involved in computer programming and software development, what makes a successful software business, and why his own company, Lucid, failed in 1994, tenyears after its inception. Perhaps the most interesting and enlightening section of the book is Gabriel's detailed look at what he believes are the lessons that can be learned from architect Christopher Alexander, whose books--including the seminal A Pattern Language--have had a profound influence on the computer programmingcommunity. Gabriel illuminates some of Alexander's key insights--the quality without a name, pattern languages, habitability, piecemeal growth--and reveals how these influential architectural ideas apply equally well to the construction of a computer program. Gabriel explains the concept ofhabitability, for example, by comparing a program to a New England farmhouse and the surrounding structures which slowly grow and are modified according to the needs and desires of the people who live and work on the farm. Programs live and grow, and their inhabitants--the programmers--need to workwith that program the way the farmer works with the homestead. Although computer scientists and software entrepreneurs will get much out of this book, the essays are accessible to everyone and will intrigue anyone curious about Silicon Valley, computer programming, or the world of high technology.

    You'll learn pragmatic ways of approaching the development process and your personal coding techniques. You'll learn about your own attitudes, issues with working on a team, and how to best manage your learning, all in an iterative, incremental, agile style. You'll see how to apply each practice, and what benefits you can expect. Bottom line: This book will make you a better developer.

    With this cookbook, you will find recipes for writing asynchronous, parallel, and reactive code in C# that enables your app or program to engage in more than one process at a time. Presented in O’Reilly’s popular problem-solution-discussion cookbook format, this guide provides ready-to-use code, along with an explanation of why and how the solution works.

    Stephen Kochan's "Programming in C" is thorough with easy-to-follow instructions that are sure to benefit beginning programmers. This book provides readers with practical examples of how the C programming language can be used with small, fast programs, similar to the programming used by large game developers such as Nintendo. If you want a one-stop-source for C programming, this book is it.The book is appropriate for all introductory-to-intermediate courses on programming in the C language, including courses covering C programming for games and small-device platforms. "Programming in C, Third Edition" is a thoroughly revised and updated edition of Steven Kochan's classic C programming tutorial: a book that has helped thousands of students master C over the past twenty years. This edition fully reflects the latest C standard and contains current source code. It has been crafted to help students master C regardless of the platform they intend to use or the applications they intend to create -- including small-device and gaming applications, where C's elegance and speed make it especially valuable.Kochan begins with the fundamentals, then covers every facet of C language programming: variables, data types, arithmetic expressions, program looping, making decisions, arrays, functions, structures, character strings, pointers, operations on bits, the preprocessors, I/O, and more. Coverage also includes chapters on working with larger programs; debugging programs; and the fundamentals of object-oriented programming. Appendices include a complete language summary, an introduction to the Standard C Library, coverage of compiling and running programs using gcc, common programming mistakes, and more.

    "Design Patterns Explained "complements the existing design patterns texts and may perform a very useful role, fitting between introductory texts such as UML Distilled and the more advanced patterns books." James Noble Leverage the quality and productivity benefits of patterns without the complexity! "Design Patterns Explained, Second Edition" is the field's simplest, clearest, most practical introduction to patterns. Using dozens of updated Java examples, it shows programmers and architects exactly how to use patterns to design, develop, and deliver software far more effectively. You'll start with a complete overview of the fundamental principles of patterns, and the role of object-oriented analysis and design in contemporary software development. Then, using easy-to-understand sample code, Alan Shalloway and James Trott illuminate dozens of today's most useful patterns: their underlying concepts, advantages, tradeoffs, implementation techniques, and pitfalls to avoid. Many patterns are accompanied by UML diagrams. Building on their best-selling First Edition, Shalloway and Trott have thoroughly updated this book to reflect new software design trends, patterns, and implementation techniques. Reflecting extensive reader feedback, they have deepened and clarified coverage throughout, and reorganized content for even greater ease of understanding. New and revamped coverage in this edition includesBetter ways to start "thinking in patterns"How design patterns can facilitate agile development using eXtreme Programming and other methodsHow to use commonality and variability analysis to design application architecturesThe key role of testing into a patterns-driven development processHow to use factories to instantiate and manage objects more effectivelyThe Object-Pool Pattern a new pattern not identified by the "Gang of Four"New study/practice questions at the end of every chapter Gentle yet thorough, this book assumes no patterns experience whatsoever. It's the ideal "first book" on patterns, and a perfect complement to Gamma's classic "Design Patterns." If you're a programmer or architect who wants the clearest possible understanding of design patterns or if you've struggled to make them work for you read this book.

    With 21st Century C, you’ll discover up-to-date techniques that are absent from every other C text available. C isn’t just the foundation of modern programming languages, it is a modern language, ideal for writing efficient, state-of-the-art applications. Learn to dump old habits that made sense on mainframes, and pick up the tools you need to use this evolved and aggressively simple language. No matter what programming language you currently champion, you’ll agree that C rocks.Set up a C programming environment with shell facilities, makefiles, text editors, debuggers, and memory checkersUse Autotools, C’s de facto cross-platform package managerLearn which older C concepts should be downplayed or deprecatedExplore problematic C concepts that are too useful to throw outSolve C’s string-building problems with C-standard and POSIX-standard functionsUse modern syntactic features for functions that take structured inputsBuild high-level object-based libraries and programsApply existing C libraries for doing advanced math, talking to Internet servers, and running databases

    The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. *NEW-Nontechnical learning material-Accompanies each part of the book. *NEW-The Internet as a sample application for intelligent systems-Added in several places including logical agents, planning, and natural language. *NEW-Increased coverage of material - Includes expanded coverage of: default reasoning and truth maintenance systems, including multi-agent/distributed AI and game theory; probabilistic approaches to learning including EM; more detailed descriptions of probabilistic inference algorithms. *NEW-Updated and expanded exercises-75% of the exercises are revised, with 100 new exercises. *NEW-On-line Java software. *Makes it easy for students to do projects on the web using intelligent agents. *A unified, agent-based approach to AI-Organizes the material around the task of building intelligent agents. *Comprehensive, up-to-date coverage-Includes a unified view of the field organized around the rational decision making pa

    Learn how easy it is to handle data as self-contained JSON-style documents, rather than as records in a relational database.Explore ways that document-oriented storage will work for your projectLearn how MongoDB’s schema-free data model handles documents, collections, and multiple databasesExecute basic write operations, and create complex queries to find data with any criteriaUse indexes, aggregation tools, and other advanced query techniquesLearn about monitoring, security and authentication, backup and repair, and moreSet up master-slave and automatic failover replication in MongoDBUse sharding to scale MongoDB horizontally, and learn how it impacts applicationsGet example applications written in Java, PHP, Python, and Ruby

    It is also the most powerful, and in some ways, the most confusing. What do accessible, content-focused standards-based web designers and front-end developers need to know? And how can we harness the power of HTML5 in today’s browsers?In this brilliant and entertaining user’s guide, Jeremy Keith cuts to the chase, with crisp, clear, practical examples, and his patented twinkle and charm.

    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.

    Programming courses usually start with theory, but this book lets you jump right into creative and fun projects. It's ideal for anyone who wants to learn basic programming, and serves as a simple introduction to graphics for people with some programming skills.Written by the founders of Processing, this book takes you through the learning process one step at a time to help you grasp core programming concepts. You'll learn how to sketch with code -- creating a program with one a line of code, observing the result, and then adding to it. Join the thousands of hobbyists, students, and professionals who have discovered this free and educational community platform.Quickly learn programming basics, from variables to objectsUnderstand the fundamentals of computer graphicsGet acquainted with the Processing software development environmentCreate interactive graphics with easy-to-follow projectsUse the Arduino open source prototyping platform to control your Processing graphics

    It was written (and illustrated!) by an all-star team:David Flanagan, bestselling author of programming language "bibles" (including JavaScript: The Definitive Guide and Java in a Nutshell) and committer to the Ruby Subversion repository.Yukihiro "Matz" Matsumoto, creator, designer and lead developer of Ruby and author of Ruby in a Nutshell, which has been expanded and revised to become this book.why the lucky stiff, artist and Ruby programmer extraordinaire. This book begins with a quick-start tutorial to the language, and then explains the language in detail from the bottom up: from lexical and syntactic structure to datatypes to expressions and statements and on through methods, blocks, lambdas, closures, classes and modules. The book also includes a long and thorough introduction to the rich API of the Ruby platform, demonstrating -- with heavily-commented example code -- Ruby's facilities for text processing, numeric manipulation, collections, input/output, networking, and concurrency. An entire chapter is devoted to Ruby's metaprogramming capabilities.The Ruby Programming Language documents the Ruby language definitively but without the formality of a language specification. It is written for experienced programmers who are new to Ruby, and for current Ruby programmers who want to challenge their understanding and increase their mastery of the language.

    Python is considered easy to learn, but there's no quicker way to mastery of the language than learning from an expert teacher. This edition of "Learning Python" puts you in the hands of two expert teachers, Mark Lutz and David Ascher, whose friendly, well-structured prose has guided many a programmer to proficiency with the language. "Learning Python," Second Edition, offers programmers a comprehensive learning tool for Python and object-oriented programming. Thoroughly updated for the numerous language and class presentation changes that have taken place since the release of the first edition in 1999, this guide introduces the basic elements of the latest release of Python 2.3 and covers new features, such as list comprehensions, nested scopes, and iterators/generators. Beyond language features, this edition of "Learning Python" also includes new context for less-experienced programmers, including fresh overviews of object-oriented programming and dynamic typing, new discussions of program launch and configuration options, new coverage of documentation sources, and more. There are also new use cases throughout to make the application of language features more concrete. The first part of "Learning Python" gives programmers all the information they'll need to understand and construct programs in the Python language, including types, operators, statements, classes, functions, modules and exceptions. The authors then present more advanced material, showing how Python performs common tasks by offering real applications and the libraries available for those applications. Each chapter ends with a series of exercises that will test your Python skills and measure your understanding."Learning Python," Second Edition is a self-paced book that allows readers to focus on the core Python language in depth. As you work through the book, you'll gain a deep and complete understanding of the Python language that will help you to understand the larger application-level examples that you'll encounter on your own. If you're interested in learning Python--and want to do so quickly and efficiently--then "Learning Python," Second Edition is your best choice.

    Displaying extraordinary creativity and programming virtuosity, Alexandrescu offers a cutting-edge approach to design that unites design patterns, generic programming, and C++, enabling programmers to achieve expressive, flexible, and highly reusable code. This book introduces the concept of generic components--reusable design templates that produce boilerplate code for compiler consumption--all within C++. Generic components enable an easier and more seamless transition from design to application code, generate code that better expresses the original design intention, and support the reuse of design structures with minimal recoding. The author describes the specific C++ techniques and features that are used in building generic components and goes on to implement industrial strength generic components for real-world applications. Recurring issues that C++ developers face in their day-to-day activity are discussed in depth and implemented in a generic way. These include: Policy-based design for flexibility Partial template specialization Typelists--powerful type manipulation structures Patterns such as Visitor, Singleton, Command, and Factories Multi-method engines For each generic component, the book presents the fundamental problems and design options, and finally implements a generic solution.