This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree- based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

    Unfortunately, most programmers frequently have a limited understanding of these essential mathematics and physics concepts. MATHEMATICS AND PHYSICS FOR PROGRAMMERS, THIRD EDITION provides a simple but thorough grounding in the mathematics and physics topics that programmers require to write algorithms and programs using a non-language-specific approach. Applications and examples from game programming are included throughout, and exercises follow each chapter for additional practice. The book's companion website provides sample code illustrating the mathematical and physics topics discussed in the book.

    Learn You a Haskell for Great Good! introduces programmers familiar with imperative languages (such as C++, Java, or Python) to the unique aspects of functional programming. Packed with jokes, pop culture references, and the author's own hilarious artwork, Learn You a Haskell for Great Good! eases the learning curve of this complex language, and is a perfect starting point for any programmer looking to expand his or her horizons. The well-known web tutorial on which this book is based is widely regarded as the best way for beginners to learn Haskell, and receives over 30,000 unique visitors monthly.

    according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog "AI Weirdness." She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans--all to understand the technology that governs so much of our daily lives.We rely on AI every day for recommendations, for translations, and to put cat ears on our selfie videos. We also trust AI with matters of life and death, on the road and in our hospitals. But how smart is AI really, and how does it solve problems, understand humans, and even drive self-driving cars?Shane delivers the answers to every AI question you've ever asked, and some you definitely haven't--like, how can a computer design the perfect sandwich? What does robot-generated Harry Potter fan-fiction look like? And is the world's best Halloween costume really "Vampire Hog Bride"?In this smart, often hilarious introduction to the most interesting science of our time, Shane shows how these programs learn, fail, and adapt--and how they reflect the best and worst of humanity. You Look Like a Thing and I Love You is the perfect book for anyone curious about what the robots in our lives are thinking.

    But if code isn't clean, it can bring a development organization to its knees. Every year, countless hours and significant resources are lost because of poorly written code. But it doesn't have to be that way. Noted software expert Robert C. Martin presents a revolutionary paradigm with Clean Code: A Handbook of Agile Software Craftsmanship . Martin has teamed up with his colleagues from Object Mentor to distill their best agile practice of cleaning code on the fly into a book that will instill within you the values of a software craftsman and make you a better programmer but only if you work at it. What kind of work will you be doing? You'll be reading code - lots of code. And you will be challenged to think about what's right about that code, and what's wrong with it. More importantly, you will be challenged to reassess your professional values and your commitment to your craft. Clean Code is divided into three parts. The first describes the principles, patterns, and practices of writing clean code. The second part consists of several case studies of increasing complexity. Each case study is an exercise in cleaning up code - of transforming a code base that has some problems into one that is sound and efficient. The third part is the payoff: a single chapter containing a list of heuristics and "smells" gathered while creating the case studies. The result is a knowledge base that describes the way we think when we write, read, and clean code. Readers will come away from this book understanding ‣ How to tell the difference between good and bad code‣ How to write good code and how to transform bad code into good code‣ How to create good names, good functions, good objects, and good classes‣ How to format code for maximum readability ‣ How to implement complete error handling without obscuring code logic ‣ How to unit test and practice test-driven development This book is a must for any developer, software engineer, project manager, team lead, or systems analyst with an interest in producing better code.

    Readers will progress from building a basic physics engine to creating intelligent moving objects and complex systems, setting the foundation for further experiments in generative design. Subjects covered include forces, trigonometry, fractals, cellular automata, self-organization, and genetic algorithms. The book's examples are written in Processing, an open-source language and development environment built on top of the Java programming language. On the book's website (http://www.natureofcode.com), the examples run in the browser via Processing's JavaScript mode.

    The library is not self-explanatory or fully consistent, and there are still some traps for the unwary. But the advantages far outweigh the problems, especially if you've got an expert book like Nicolai Josuttis' C++ Standard Library to help you. Josuttis starts with an overview of the standard library, and its key interrelationships with the core language. He presents detailed coverage of the STL, the most powerful, complex, and exciting part of the library; then covers special containers, strings, numeric classes, and internationalization; and helps you get more out of a component you're probably already using: the IOStream library. Every component description includes purpose, design, code examples, practical scenarios, pitfalls, and in most cases, reference sources. Whether you need a tutorial or reference, this book delivers the goods.— (Bill Camarda, bn.com, editor)

    The author's take on the essence of Java as a new programming language and the thorough introduction to Java's features make this a worthwhile tutorial. Thinking in Java begins a little esoterically, with the author's reflections on why Java is new and better. (This book's choice of font for chapter headings is remarkably hard on the eyes.) The author outlines his thoughts on why Java will make you a better programmer, without all the complexity. The book is better when he presents actual language features. There's a tutorial to basic Java types, keywords, and operators. The guide includes extensive source code that is sometimes daunting (as with the author's sample code for all the Java operators in one listing.) As such, this text will be most useful for the experienced developer. The text then moves on to class design issues, when to use inheritance and composition, and related topics of information hiding and polymorphism. (The treatment of inner classes and scoping will likely seem a bit overdone for most readers.) The chapter on Java collection classes for both Java Developer's Kit (JDK) 1.1 and the new classes, such as sets, lists, and maps, are much better. There's material in this chapter that you are unlikely to find anywhere else. Chapters on exception handling and programming with type information are also worthwhile, as are the chapters on the new Swing interface classes and network programming. Although it adopts somewhat of a mixed-bag approach, Thinking in Java contains some excellent material for the object-oriented developer who wants to see what all the fuss is about with Java.

    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.

    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.

    You'll master the Unity toolset from the ground up, adding the skills you need to go from application coder to game developer. Based on Unity version 5.About the BookThis book helps readers build successful games with the Unity game development platform. You will use the powerful C# language, Unity's intuitive workflow tools, and a state-of-the-art rendering engine to build and deploy mobile, desktop, and console games. Unity's single codebase approach minimizes inefficient switching among development tools and concentrates your attention on making great interactive experiences.Unity in Action teaches you how to write and deploy games. You'll master the Unity toolset from the ground up, adding the skills you need to go from application coder to game developer. Each sample project illuminates specific Unity features and game development strategies. As you read and practice, you'll build up a well-rounded skill set for creating graphically driven 2D and 3D game applications.You'll need to know how to program, in C# or a similar OO language. No previous Unity experience or game development knowledge is assumed.

    This third edition has been updated toreflect current best practices andthe abundance of changes introduced by the latest version of thelanguage, Python 2.5.Whether you're a novice or an advancedpractitioner, you'll find thisrefreshed book more than lives up to its reputation. "ProgrammingPython," 3rd Edition, teaches you the rightway to code. It explains Python language syntax and programmingtechniques in a clear and concisemanner, with numerous examples that illustrate both correct usage andcommon idioms. By reading thiscomprehensive guide, you'll learn how to apply Python in real-worldproblem domains such as: GUI programmingInternet scriptingParallel processingDatabase managementNetworked applications"Programming Python," Third Edition coverseach of thesetarget domainsgradually, beginning with in-depth discussions of core concepts andthen progressing toward completeprograms. Large examples do appear, but only after you've learnedenough to understand their techniques andcode.Along the way, you'll also learn how to use the Python language inrealistically scaled programs--concepts such as Object-Oriented Programming (OOP) and code reuseare recurring side themes throughout thistext. If you're interested in Python programming, then this O'Reillyclassic needs to be within arm's reach. Thewealth of practical advice, snippets of code, and patterns of programdesign can all be put into use on adaily basis--making your life easier and more productive.Reviews of the second edition:.".".about as comprehensive as any book can be.""--Dr. Dobb's Journal""If the language had manuals, they would undoubtedlybe the texts from O'Reilly...'Learning Python' and 'Programming Python'are definitive treatments.""--SD Times

     -Byte, September 1995 I can't begin to tell you how many pleasurable hours of study and recreation they have afforded me! I have pored over them in cars, restaurants, at work, at home... and even at a Little League game when my son wasn't in the line-up. -Charles Long If you think you're a really good programmer... read [Knuth's] Art of Computer Programming... You should definitely send me a resume if you can read the whole thing. -Bill Gates It's always a pleasure when a problem is hard enough that you have to get the Knuths off the shelf. I find that merely opening one has a very useful terrorizing effect on computers. -Jonathan Laventhol This first volume in the series begins with basic programming concepts and techniques, then focuses more particularly on information structures-the representation of information inside a computer, the structural relationships between data elements and how to deal with them efficiently. Elementary applications are given to simulation, numerical methods, symbolic computing, software and system design. Dozens of simple and important algorithms and techniques have been added to those of the previous edition. The section on mathematical preliminaries has been extensively revised to match present trends in research. Ebook (PDF version) produced by Mathematical Sciences Publishers (MSP), http: //msp.org

    The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to take a hard pass on Knuth's brilliant but impenetrable theories and the dense multi-page proofs you'll find in most textbooks, this is the book for you. This fully-illustrated and engaging guide makes it easy for you to learn how to use algorithms effectively in your own programs.Grokking Algorithms is a disarming take on a core computer science topic. In it, you'll learn how to apply common algorithms to the practical problems you face in day-to-day life as a programmer. You'll start with problems like sorting and searching. As you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression or artificial intelligence. Whether you're writing business software, video games, mobile apps, or system utilities, you'll learn algorithmic techniques for solving problems that you thought were out of your grasp. For example, you'll be able to:Write a spell checker using graph algorithmsUnderstand how data compression works using Huffman codingIdentify problems that take too long to solve with naive algorithms, and attack them with algorithms that give you an approximate answer insteadEach carefully-presented example includes helpful diagrams and fully-annotated code samples in Python. By the end of this book, you will know some of the most widely applicable algorithms as well as how and when to use them.

    This highly anticipated fourth edition of the most ...Download Link : readmeaway.com/download?i=0128042915            0128042915 Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF by Ian H. WittenRead Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems) PDF from Morgan Kaufmann,Ian H. WittenDownload Ian H. Witten's PDF E-book Data Mining: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series in Data Management Systems)