Through concrete examples and jargon-free explanations, this book teaches you how to apply functional programming to real-life development tasks. The book includes insightful comparisons to object-oriented or imperative programming, which will allow you to ease into functional design. Moreover, you'll learn a repertoire of techniques including function chaining and pipelining, recursion, currying, binding, functional composition, lazy evaluation, fluent error handling, memoization, and much more. By the end of the book, you'll think about application design in a fresh new way.About the technologyAs web developers build increasingly complex applications in JavaScript, the code base for these projects can become exponentially larger and harder to maintain. The result? Application performance suffers, and readability and extensibility are severely compromised. For applications like these, Functional Programming provides a saner approach, allowing you to write elegant, readable code that raises the level of abstraction while being less prone to errors. Although not a "pure" functional language, JavaScript's native functional capabilities unlock access to proven functional programming techniques and practices.What's insideFoundations of functional programming and designExplore JavaScript's functional programming capabilities and the functional library ecosystemCreate more reliable code by embracing immutabilityLearn to write code that's easier to reason aboutSeparate core logic from program structure to write extensible codeAdopt a new approach to error handling and testingApply functional programming to solve real-world problemsAbout the readerReaders need to be comfortable with JavaScript programming and object-oriented design. No previous experience with functional programming is required.About the authorLuis Atencio is a Staff Software Engineer for Citrix Systems in Ft. Lauderdale, FL. He develops and architects applications leveraging Java, PHP, and JavaScript platforms. Luis is very involved in the community and has presented at local meet-ups. He blogs about software engineering at luisatencio.net and writes articles for PHP magazines and DZone. Follow Luis on twitter at @luijar.

    What they don't realize—and what Daniel Hillis's short book brilliantly demonstrates—is that computers' seemingly complex operations can be broken down into a few simple parts that perform the same simple procedures over and over again.Computer wizard Hillis offers an easy-to-follow explanation of how data is processed that makes the operations of a computer seem as straightforward as those of a bicycle. Avoiding technobabble or discussions of advanced hardware, the lucid explanations and colorful anecdotes in The Pattern on the Stone go straight to the heart of what computers really do.Hillis proceeds from an outline of basic logic to clear descriptions of programming languages, algorithms, and memory. He then takes readers in simple steps up to the most exciting developments in computing today—quantum computing, parallel computing, neural networks, and self-organizing systems.Written clearly and succinctly by one of the world's leading computer scientists, The Pattern on the Stone is an indispensable guide to understanding the workings of that most ubiquitous and important of machines: the computer.

    As a result, functional code is easier to test and reuse, simpler to parallelize, and less prone to bugs. Scala is an emerging JVM language that offers strong support for FP. Its familiar syntax and transparent interoperability with existing Java libraries make Scala a great place to start learning FP.Functional Programming in Scala is a serious tutorial for programmers looking to learn FP and apply it to the everyday business of coding. The book guides readers from basic techniques to advanced topics in a logical, concise, and clear progression. In it, they'll find concrete examples and exercises that open up the world of functional programming.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.

    Now that machine learning is thriving, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn how to use a range of techniques, starting with simple Linear Regression and progressing to Deep Neural Networks. If you have some programming experience and you’re ready to code a machine learning project, this guide is for you.This hands-on book shows you how to use:Scikit-Learn, an accessible framework that implements many algorithms efficiently and serves as a great machine learning entry pointTensorFlow, a more complex library for distributed numerical computation, ideal for training and running very large neural networksPractical code examples that you can apply without learning excessive machine learning theory or algorithm details

    This book covers relevant geometric principles and how to represent objects algebraically so they can be computed and applied. Recent major developments in the theory and practice of scene reconstruction are described in detail in a unified framework. Richard Hartley and Andrew Zisserman provide comprehensive background material and explain how to apply the methods and implement the algorithms. First Edition HB (2000): 0-521-62304-9

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

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    The books also provides a companion web site that provides the toold and materials necessary to build the hardware and software.

    This instantly useful book is packed with creative examples and powerful best practices that will sharpen your technical skills and inspire your sense of design.Foreword by Chris Coyier, Cofounder of CodePen.Dig even deeper into the secrets of CSS with our video course CSS in Depth in Motion, available exclusively at Manning.com (www.manning.com/livevideo/css-in-dept...)!Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.About the TechnologySome websites really pop. They look great, they're visually consistent, and they feel interactive and responsive. You can bet their developers knew CSS in depth. CSS specifies everything from the structural layout of page elements to their individual look and feel. True masters know the patterns of CSS development, the techniques to implement them, and the subtle touches that result in beautiful typography, fluid transitions, and balanced graphics. Join them!About the BookCSS in Depth exposes you to a world of CSS techniques that range from clever to mind-blowing. This instantly useful book is packed with creative examples and powerful best practices that will sharpen your technical skills and inspire your sense of design. You'll gain new insights into familiar features like floats and units, and experiment with emerging ideas like responsive design and pattern libraries. Bottom line: this book will make you a better web designer and your apps will look fantastic!What's InsideAvoid common CSS pitfallsMaster misunderstood conceptsUse flexbox and grid layoutResponsive designs for any deviceCode for reuse and maintainabilityAbout the ReaderWritten for web developers who know the basics of CSS and HTML.About the AuthorKeith J. Grant is a senior web developer who builds and maintains web applications and websites, including The New York Stock Exchange site.Table of ContentsPART 1 - REVIEWING THE FUNDAMENTALSCascade, specificity, and inheritanceWorking with relative unitsMastering the box modelPART 2 - MASTERING LAYOUTMaking sense of floatsFlexboxGrid layoutPositioning and stacking contextsResponsive designPART 3 - CSS AT SCALEModular CSSPattern librariesPART 4 - ADVANCED TOPICSBackgrounds, shadows, and blend modesContrast, color, and spacingTypographyTransitionsTransformsAnimations

     Rails(TM) AntiPatterns identifies these widespread Rails code and design problems, explains why they're bad and why they happen--and shows exactly what to do instead.The book is organized into concise, modular chapters--each outlines a single common AntiPattern and offers detailed, cookbook-style code solutions that were previously difficult or impossible to find. Leading Rails developers Chad Pytel and Tammer Saleh also offer specific guidance for refactoring existing bad code or design to reflect sound object-oriented principles and established Rails best practices. With their help, developers, architects, and testers can dramatically improve new and existing applications, avoid future problems, and establish superior Rails coding standards throughout their organizations.This book will help you understand, avoid, and solve problems withModel layer code, from general object-oriented programming violations to complex SQL and excessive redundancy Domain modeling, including schema and database issues such as normalization and serialization View layer tools and conventions Controller-layer code, including RESTful code Service-related APIs, including timeouts, exceptions, backgrounding, and response codes Third-party code, including plug-ins and gems Testing, from test suites to test-driven development processes Scaling and deployment Database issues, including migrations and validations System design for "graceful degradation" in the real world

    It presents a learning journey, not definitive guidance. It describes the experiences of a development team with no prior CQRS proficiency in building, deploying (to Windows Azure), and maintaining a sample real-world, complex, enterprise system to showcase various CQRS and ES concepts, challenges, and techniques.The development team did not work in isolation; we actively sought input from industry experts and from a wide group of advisors to ensure that the guidance is both detailed and practical.The CQRS pattern and event sourcing are not mere simplistic solutions to the problems associated with large-scale, distributed systems. By providing you with both a working application and written guidance, we expect you’ll be well prepared to embark on your own CQRS journey.

    This book offers numerous examples to help you avoid the many pitfalls that entrap new and not-so-new database designers. Through the help of use cases and class diagrams modeled in the UML, youll learn how to discover and represent the details and scope of the problem in question.Database design is not an exact science, and solid database design principles and examples help demonstrate the consequences of simplifications and pragmatic decisions. The rationale is to try to keep it simple, but allow room for development as situations change or resources permit. The book also features an introduction for implementing the final design in a relational database.

    Land of Lisp brings the language into the real world, teaching Lisp by showing readers how to write several complete Lisp-based games, including a text adventure, an evolution simulation, and a robot battle. While building these games, readers learn the core concepts of Lisp programming, such as data types, recursion, input/output, object-oriented programming, and macros. And thanks to the power of Lisp, the code is short. Rather than bogging things down with reference information that is easily found online, Land of Lisp focuses on using Lisp for real programming. The book is filled with the author Conrad Barski's famous Lisp cartoons, featuring the Lisp alien and other zany characters.

    This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.You'll work with a case study throughout the book to help you learn the entire data analysis process—from collecting data and generating statistics to identifying patterns and testing hypotheses. Along the way, you'll become familiar with distributions, the rules of probability, visualization, and many other tools and concepts.Develop your understanding of probability and statistics by writing and testing codeRun experiments to test statistical behavior, such as generating samples from several distributionsUse simulations to understand concepts that are hard to grasp mathematicallyLearn topics not usually covered in an introductory course, such as Bayesian estimationImport data from almost any source using Python, rather than be limited to data that has been cleaned and formatted for statistics toolsUse statistical inference to answer questions about real-world data

    Now delete that picture. In Once Upon an Algorithm, Martin Erwig explains computation as something that takes place beyond electronic computers, and computer science as the study of systematic problem solving. Erwig points out that many daily activities involve problem solving. Getting up in the morning, for example: You get up, take a shower, get dressed, eat breakfast. This simple daily routine solves a recurring problem through a series of well-defined steps. In computer science, such a routine is called an algorithm.Erwig illustrates a series of concepts in computing with examples from daily life and familiar stories. Hansel and Gretel, for example, execute an algorithm to get home from the forest. The movie Groundhog Day illustrates the problem of unsolvability; Sherlock Holmes manipulates data structures when solving a crime; the magic in Harry Potter's world is understood through types and abstraction; and Indiana Jones demonstrates the complexity of searching. Along the way, Erwig also discusses representations and different ways to organize data; "intractable" problems; language, syntax, and ambiguity; control structures, loops, and the halting problem; different forms of recursion; and rules for finding errors in algorithms.This engaging book explains computation accessibly and shows its relevance to daily life. Something to think about next time we execute the algorithm of getting up in the morning.