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

    The rapid maturation of PHP has created a skeptical population of users from more traditional enterprise languages who question the readiness and ability of PHP to scale, as well as a large population of PHP developers without formal computer science backgrounds who have learned through the hands-on experimentation while developing small and midsize applications in PHP. While there are many books on learning PHP and developing small applications with it, there is a serious lack of information on scaling PHP for large-scale, business-critical systems. Schlossnagle's Advanced PHP Programming fills that void, demonstrating that PHP is ready for enterprise Web applications by showing the reader how to develop PHP-based applications for maximum performance, stability, and extensibility.

    Freeman, Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of TechnologyLearning OpenCV puts you in the middle of the rapidly expanding field of computer vision. Written by the creators of the free open source OpenCV library, this book introduces you to computer vision and demonstrates how you can quickly build applications that enable computers to "see" and make decisions based on that data. Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time.Learning OpenCV will teach any developer or hobbyist to use the framework quickly with the help of hands-on exercises in each chapter. This book includes:A thorough introduction to OpenCV Getting input from cameras Transforming images Segmenting images and shape matching Pattern recognition, including face detection Tracking and motion in 2 and 3 dimensions 3D reconstruction from stereo vision Machine learning algorithms Getting machines to see is a challenging but entertaining goal. Whether you want to build simple or sophisticated vision applications, Learning OpenCV is the book you need to get started.

    But facing the sea change that AI will bring can be paralyzing. How should companies set strategies, governments design policies, and people plan their lives for a world so different from what we know? In the face of such uncertainty, many analysts either cower in fear or predict an impossibly sunny future.But in Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policy makers, investors, and entrepreneurs.When AI is framed as cheap prediction, its extraordinary potential becomes clear: Prediction is at the heart of making decisions under uncertainty. Our businesses and personal lives are riddled with such decisions. Prediction tools increase productivity--operating machines, handling documents, communicating with customers. Uncertainty constrains strategy. Better prediction creates opportunities for new business structures and strategies to compete. Penetrating, fun, and always insightful and practical, Prediction Machines follows its inescapable logic to explain how to navigate the changes on the horizon. The impact of AI will be profound, but the economic framework for understanding it is surprisingly simple.

    Admittedly, computers now play chess at the grandmaster level, but do they understand the game as we do? Can a computer eventually do everything a human mind can do? In this absorbing and frequently contentious book, Roger Penrose--eminent physicist and winner, with Stephen Hawking, of the prestigious Wolf prize--puts forward his view that there are some facets of human thinking that can never be emulated by a machine. Penrose examines what physics and mathematics can tell us about how the mind works, what they can't, and what we need to know to understand the physical processes of consciousness. He is among a growing number of physicists who think Einstein wasn't being stubborn when he said his little finger told him that quantum mechanics is incomplete, and he concludes that laws even deeper than quantum mechanics are essential for the operation of a mind. To support this contention, Penrose takes the reader on a dazzling tour that covers such topics as complex numbers, Turing machines, complexity theory, quantum mechanics, formal systems, Godel undecidability, phase spaces, Hilbert spaces, black holes, white holes, Hawking radiation, entropy, quasicrystals, the structure of the brain, and scores of other subjects. The Emperor's New Mind will appeal to anyone with a serious interest in modern physics and its relation to philosophical issues, as well as to physicists, mathematicians, philosophers and those on either side of the AI debate.

    It has found adherents in Silicon Valley billionaires Ray Kurzweil and Peter Diamandis. Google has entered the picture, establishing a bio-tech subsidiary aimed at solving the problem of aging.In To Be a Machine, journalist Mark O'Connell takes a headlong dive into this burgeoning movement. He travels to the laboratories, conferences, and basements of today's foremost transhumanists, where he's presented with the staggering possibilities and moral quandaries of new technologies like mind uploading, artificial superintelligence, cryonics, and device implants.A contributor to Slate, The New Yorker, and The New York Times Magazine, O'Connell serves as a sharp and lively guide to the outer limits of technology in the twenty first century. In investigating what it means to be a machine, he offers a surprising, singular meditation on what it means to be human."

    While this remains a remote possibility, rapid progress on AI in this century is already profoundly changing our world. Yet the public debate and media hype is still largely centred on unlikely prospects from sentient machines to dystopian robot takeovers.In this lively and clear-headed guide, Michael Wooldridge brings a healthy injection of humility to an overhyped field and changes the prevailing narrative on AI, revealing how these anxieties distract us from the more immediate risks that this transformative technology poses - from algorithmic bias to fake news. He also shows us how they overlook the true life-changing potential of the field he loves.The Road to Conscious Machines gives us the real story of AI, through all its booms and many busts, elucidating the discoveries of its greatest pioneers from Alan Turing to Demis Hassabis, and showing us what today's AI researchers actually think and do. As this deft and detailed survey reveals, AI appeals to fundamental questions about what it means to be human; so too do the failures and limitations of its past.

    The timely provision of relevant information with minimal 'noise' is critical to modern society and this is what information retrieval (IR) is all about. It is a dynamic subject, with current changes driven by the expansion of the World Wide Web, the advent of modern and inexpensive graphical user interfaces and the development of reliable and low-cost mass storage devices. Modern Information Retrieval discusses all these changes in great detail and can be used for a first course on IR as well as graduate courses on the topic.The organization of the book, which includes a comprehensive glossary, allows the reader to either obtain a broad overview or detailed knowledge of all the key topics in modern IR. The heart of the book is the nine chapters written by Baeza-Yates and Ribeiro-Neto, two leading exponents in the field. For those wishing to delve deeper into key areas there are further state-of-the-art ch

    

    Drawing on his experience as a medical researcher, Vickers blends insightful explanations and humor, with minimal math, to help readers understand and interpret the statistics they read every day. Describing data; Data distributions; Variation of study results: confidence intervals; Hypothesis testing; Regression and decision making; Some common statistical errors, and what they teach us For all readers interested in statistics.

    Cassandra: The Definitive Guide provides the technical details and practical examples you need to assess this database management system and put it to work in a production environment.Author Eben Hewitt demonstrates the advantages of Cassandra's nonrelational design, and pays special attention to data modeling. If you're a developer, DBA, application architect, or manager looking to solve a database scaling issue or future-proof your application, this guide shows you how to harness Cassandra's speed and flexibility.Understand the tenets of Cassandra's column-oriented structureLearn how to write, update, and read Cassandra dataDiscover how to add or remove nodes from the cluster as your application requiresExamine a working application that translates from a relational model to Cassandra's data modelUse examples for writing clients in Java, Python, and C#Use the JMX interface to monitor a cluster's usage, memory patterns, and moreTune memory settings, data storage, and caching for better performance

    

    Holland dramatically shows us that the “emergence” of order from disorder has much to teach us about life, mind and organizations. Creative activities in both the arts and the sciences depend upon an ability to model the world. The most creative of those models exhibits emergent properties, so that “what comes out is more than what goes in.” From the ingenious checkers-playing computer that started beating its creator in game after game, to the emotive creations of the poet, Emergence shows that Holland’s theory successfully predicts many complex behaviors in art and science.

    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.

    JavaScript lets designers add sparkle and life to web pages, while more complex JavaScript has led to the rise of Ajax -- the latest rage in web development that allows developers to create powerful and more responsive applications in the browser window."Learning JavaScript" introduces this powerful scripting language to web designers and developers in easy-to-understand terms. Using the latest examples from modern browser development practices, this book teaches you how to integrate the language with the browser environment, and how to practice proper coding techniques for standards-compliant web sites. By the end of the book, you'll be able to use all of the JavaScript language and many of the object models provided by web browsers, and you'll even be able to create a basic Ajax application.