Artificial Intelligence is the most exciting technology of the century, and Deep Learning is, quite literally, the "brain" behind the world's smartest Artificial Intelligence systems out there. Grokking Deep Learning is the perfect place to begin the deep learning journey. Rather than just learning the "black box" API of some library or framework, readers will actually understand how to build these algorithms completely from scratch. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated field. Large companies such as Google, Microsoft, and Facebook have taken notice, and are actively growing in-house deep learning teams. For the rest of us however, deep learning is still a pretty complex and difficult subject to grasp. If you have a basic understanding of what machine learning is, have familiarity with the Python programming language, and have some mathematical background with calculus, this book will help you get started.
Summary Grokking Algorithms is a fully illustrated, friendly guide that teaches you how to apply common algorithms to the practical problems you face every day as a programmer. You'll start with sorting and searching and, as you build up your skills in thinking algorithmically, you'll tackle more complex concerns such as data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. Learning about algorithms doesn't have to be boring! Get a sneak peek at the fun, illustrated, and friendly examples you'll find in Grokking Algorithms on Manning Publications' YouTube channel. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology An algorithm is nothing more than a step-by-step procedure for solving a problem. The algorithms you'll use most often as a programmer have already been discovered, tested, and proven. If you want to understand them but refuse to slog through dense multipage proofs, this is the book for you. This fully illustrated and engaging guide makes it easy to learn how to use the most important algorithms effectively in your own programs. About the Book Grokking Algorithms is a friendly take on this core computer science topic. In it, you'll learn how to apply common algorithms to the practical programming problems you face every day. You'll start with tasks like sorting and searching. As you build up your skills, you'll tackle more complex problems like data compression and artificial intelligence. Each carefully presented example includes helpful diagrams and fully annotated code samples in Python. By the end of this book, you will have mastered widely applicable algorithms as well as how and when to use them. What's Inside Covers search, sort, and graph algorithms Over 400 pictures with detailed walkthroughs Performance trade-offs between algorithms Python-based code samples About the Reader This easy-to-read, picture-heavy introduction is suitable for self-taught programmers, engineers, or anyone who wants to brush up on algorithms. About the Author Aditya Bhargava is a Software Engineer with a dual background in Computer Science and Fine Arts. He blogs on programming at adit.io. Table of Contents Introduction to algorithms Selection sort Recursion Quicksort Hash tables Breadth-first search Dijkstra's algorithm Greedy algorithms Dynamic programming K-nearest neighbors
Deep learning is applicable to a widening range of artificial intelligence problems, such as image classification, speech recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python is structured around a series of practical code examples that illustrate each new concept introduced and demonstrate best practices. By the time you reach the end of this book, you will have become a Keras expert and will be able to apply deep learning in your own projects. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J’s workflow tool Learn how to use DL4J natively on Spark and Hadoop
Author: Casper Harteveld
Publisher: Springer Science & Business Media
Release Date: 2011-02-26
Many designers, policy makers, teachers, and other practitioners are beginning to understand the usefulness of using digital games beyond entertainment. Games have been developed for teaching, recruiting and to collect data to improve search engines. This book examines the fundamentals of designing any game with a serious purpose and provides a way of thinking on how to design one successfully. The reader will be introduced to a design philosophy called “Triadic Game Design.”; a theory that all games involve three worlds: the worlds of Reality, Meaning, and Play. Each world is affiliated with aspects. A balance needs to be found within and between the three worlds. Such a balance is difficult to achieve, during the design many tensions will arise, forcing designers to make trade-offs. To deal with these tensions and to ensure that the right decisions are made to create a harmonic game, a frame of reference is needed. This is what Triadic Game Design offers.
Author: John Paul Mueller
Publisher: John Wiley & Sons
Release Date: 2017-02-21
Algorithms For Dummies addresses people who are interested in algorithms without requiring them to pursue a PhD on the subject. The idea is that we already live in a world where algorithms are behind most of the technology we use, so we need to understand them better. In order to make this happen, the book would present the major areas comprising algorithms (optimization, sort, graph, hash, string, dynamic programming) telling the history behind algorithms, presenting actual applications, simply explaining the nuts and bolts of the algorithm. For readers who are interested, the book presents an implementation in Python and some experiments with them, so they can get hands on experience developing an algorithm from start to finish. The goal is to create an accessible introduction to algorithms, so that the reader can understand how the key algorithms work and how to benefit from algorithms when working on projects and implementing them in business strategy.
ReactiveX is the common tongue of the reactive programming world. It's a new programming paradigm applied to infinite scenarios using any popular programming language. To really understand Rx, you need to rewire your brain to see the world differently, and we're here to help you. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Grokking ReactiveX is a practical book that teaches readers how to solve complex problems elegantly and with few lines of code. To make learning easier, each chapter introduces a new concept and then immediately demonstrates how to use it. Following carefully-selected examples with thorough, well-paced explanations, readers will immerse themselves in ReactiveX, concept by concept.
Special Features: Learning Elements:· How to create recommendations just like those on Netflix and Amazon· How to implement Google's Pagerank algorithm· How to discover matches on social-networking sites· How to organize the discussions on your favorite news group· How to select topics of interest from shared bookmarks· How to leverage user clicks· How to categorize emails based on their content· How to build applications that do targeted advertising· How to implement fraud detection About The Book: Algorithms of the Intelligent Web is an example-driven blueprint for creating applications that collect, analyze, and act on the massive quantities of data users leave in their wake as they use the web. You'll learn how to build Amazon- and Netflix-style recommendation engines, and how the same techniques apply to people matches on social-networking sites. See how click-trace analysis can result in smarter ad rotations. With a plethora of examples and extensive detail, this book shows you how to build Web 2.0 applications that are as smart as your users.
Now in full color, the 10th anniversary edition of this classic book takes you deep into the influences that underlie modern video games, and examines the elements they share with traditional games such as checkers. At the heart of his exploration, veteran game designer Raph Koster takes a close look at the concept of fun and why it’s the most vital element in any game. Why do some games become boring quickly, while others remain fun for years? How do games serve as fundamental and powerful learning tools? Whether you’re a game developer, dedicated gamer, or curious observer, this illustrated, fully updated edition helps you understand what drives this major cultural force, and inspires you to take it further. You’ll discover that: Games play into our innate ability to seek patterns and solve puzzles Most successful games are built upon the same elements Slightly more females than males now play games Many games still teach primitive survival skills Fictional dressing for modern games is more developed than the conceptual elements Truly creative designers seldom use other games for inspiration Games are beginning to evolve beyond their prehistoric origins
Author: Jeff Smith
Publisher: Manning Publications
Release Date: 2017-05-31
Machine learning applications autonomously reason about data at massive scale. It's important that they remain responsive in the face of failure and changes in load. But machine learning systems are different than other applications when it comes to testing, building, deploying, and monitoring. Reactive Machine Learning Systems teaches readers how to implement reactive design solutions in their machine learning systems to make them as reliable as a well-built web app. Using Scala and powerful frameworks such as Spark, MLlib, and Akka, they'll learn to quickly and reliably move from a single machine to a massive cluster. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Author: Robert A Heinlein
Release Date: 2016-10-25
A deluxe hardcover edition of the most famous science-fiction novel of all time--part of Penguin Galaxy, a collectible series of six sci-fi/fantasy classics, featuring a series introduction by Neil Gaiman A human raised on Mars, Valentine Michael Smith has just arrived on planet Earth. Among his people for the first time, he struggles to understand the social mores and prejudices of human nature that are so alien to him, while his own "psi" powers--including telepathy, clairvoyance, telekenesis, and teleportation--make him a type of messiah figure among humans. Stranger in a Strange Land grew from a cult favorite to a bestseller to a classic in a few short years. The story of the man from Mars who taught humankind grokking and water-sharing--and love--it is Robert A. Heinlein's masterpiece. Penguin Galaxy Six of our greatest masterworks of science fiction and fantasy, in dazzling collector-worthy hardcover editions, and featuring a series introduction by #1 New York Times bestselling author Neil Gaiman, Penguin Galaxy represents a constellation of achievement in visionary fiction, lighting the way toward our knowledge of the universe, and of ourselves. From historical legends to mythic futures, monuments of world-building to mind-bending dystopias, these touchstones of human invention and storytelling ingenuity have transported millions of readers to distant realms, and will continue for generations to chart the frontiers of the imagination. The Once and Future King by T. H. White Stranger in a Strange Land by Robert A. Heinlein Dune by Frank Herbert 2001: A Space Odyssey by Arthur C. Clarke The Left Hand of Darkness by Ursula K. Le Guin Neuromancer by William Gibson For more than seventy years, Penguin has been the leading publisher of classic literature in the English-speaking world. With more than 1,700 titles, Penguin Classics represents a global bookshelf of the best works throughout history and across genres and disciplines. Readers trust the series to provide authoritative texts enhanced by introductions and notes by distinguished scholars and contemporary authors, as well as up-to-date translations by award-winning translators.