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

    The LEGO MINDSTORMS NXT 2.0 Discovery Book is the complete, illustrated, beginner's guide to MINDSTORMS that you've been looking for. The crystal clear instructions in the Discovery Book will show you how to harness the capabilities of the NXT 2.0 set to build and program your own robots. Author and robotics instructor Laurens Valk walks you through the set, showing you how to use its various pieces, and how to use the NXT software to program robots. Interactive tutorials make it easy for you to reach an advanced level of programming as you learn to build robots that move, monitor sensors, and use advanced programming techniques like data wires and variables. You'll build eight increasingly sophisticated robots like the Strider (a six-legged walking creature), the CCC (a climbing vehicle), the Hybrid Brick Sorter (a robot that sorts by color and size), and the Snatcher (an autonomous robotic arm). Numerous building and programming challenges throughout encourage you to think creatively and to apply what you've learned as you develop the skills essential to creating your own robots.Requirements: One LEGO MINDSTORMS NXT 2.0 set (#8547)FeaturesA complete introduction to LEGO MINDSTORMS NXT 2.0 Building and programming instructions for eight innovative robots 50 sample programs and 72 programming challenges (ranging from easy to hard) encourage you to explore newly learned programming techniques 15 building challenges expand on the robot designs and help you develop ideas for new robotsWho is this book for? This is a perfect introduction for those new to building and programming with the LEGO MINDSTORMS NXT 2.0 set. The book also includes intriguing robot designs and useful programming tips for more seasoned MINDSTORMS builders.

    During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.

    It is within the realm of possibility that their work may usher in a change in global economics as profound as the Industrial Revolution. As may be expected, press reports dealing with asteroid mining have been numerous, ranging in scope from short and breezy to broad and serious, and in quality from accurate to impressionistic to simply uninformed. There is good reason to be curious about what may be the biggest game-changer in human economic history. And there is good reason to look closely at the underlying science and engineering that form the foundation of this work.

    He takes you inside a typical interview by exploring the various types of case questions and he shares with you the acclaimed Ivy Case System which will give you the confidence to answer even the most sophisticated cases. The book includes over 40 strategy cases, ten case starts exercises and 21 ways to cut costs, plus much, much more!

    Its techniques are widely applied in engineering, science, finance, and commerce. This book is designed for a short course on machine learning. It is a short course, not a hurried course. From over a decade of teaching this material, we have distilled what we believe to be the core topics that every student of the subject should know. We chose the title `learning from data' that faithfully describes what the subject is about, and made it a point to cover the topics in a story-like fashion. Our hope is that the reader can learn all the fundamentals of the subject by reading the book cover to cover. ---- Learning from data has distinct theoretical and practical tracks. In this book, we balance the theoretical and the practical, the mathematical and the heuristic. Our criterion for inclusion is relevance. Theory that establishes the conceptual framework for learning is included, and so are heuristics that impact the performance of real learning systems. ---- Learning from data is a very dynamic field. Some of the hot techniques and theories at times become just fads, and others gain traction and become part of the field. What we have emphasized in this book are the necessary fundamentals that give any student of learning from data a solid foundation, and enable him or her to venture out and explore further techniques and theories, or perhaps to contribute their own. ---- The authors are professors at California Institute of Technology (Caltech), Rensselaer Polytechnic Institute (RPI), and National Taiwan University (NTU), where this book is the main text for their popular courses on machine learning. The authors also consult extensively with financial and commercial companies on machine learning applications, and have led winning teams in machine learning competitions.

    Fat, they told us, was the enemy. Then it was salt, then sugar, then cholesterol... and on it goes. Americans listened and they lost -- but not their excess fat. What they lost was their health and waistlines. Americans are the fattest people on earth... and why? Mainly because of the food they eat. In this scientific and revolutionary book, based on Nobel Prize-winning research, medical visionary and former Massachusetts Institute of Technology researcher Dr. Barry Sears makes peak physical and mental performance, as well as permanent fat loss, simple for you to understand and achieve. With lists of good and bad carbohydrates, easy-to-follow food blocks and delicious recipes, The Zone provides all you need to begin your journey toward permanent fat loss, great health and all-round peak performance. In balance, your body will not only burn fat, but you'll fight heart disease, diabetes, PMS, chronic fatigue, depression and cancer, as well as alleviate the painful symptoms of diseases such as multiple sclerosis and HIV. This Zone state of exceptional health is well-known to champion athletes. Your own journey toward it can begin with your next meal. You will no longer think of food as merely an item of pleasure or a means to appease hunger. Food is your medicine and your ticket to that state of ultimate body balance, strength and great health: the Zone.

    The framework of probabilistic graphical models, presented in this book, provides a general approach for this task. The approach is model-based, allowing interpretable models to be constructed and then manipulated by reasoning algorithms. These models can also be learned automatically from data, allowing the approach to be used in cases where manually constructing a model is difficult or even impossible. Because uncertainty is an inescapable aspect of most real-world applications, the book focuses on probabilistic models, which make the uncertainty explicit and provide models that are more faithful to reality.Probabilistic Graphical Models discusses a variety of models, spanning Bayesian networks, undirected Markov networks, discrete and continuous models, and extensions to deal with dynamical systems and relational data. For each class of models, the text describes the three fundamental cornerstones: representation, inference, and learning, presenting both basic concepts and advanced techniques. Finally, the book considers the use of the proposed framework for causal reasoning and decision making under uncertainty. The main text in each chapter provides the detailed technical development of the key ideas. Most chapters also include boxes with additional material: skill boxes, which describe techniques; case study boxes, which discuss empirical cases related to the approach described in the text, including applications in computer vision, robotics, natural language understanding, and computational biology; and concept boxes, which present significant concepts drawn from the material in the chapter. Instructors (and readers) can group chapters in various combinations, from core topics to more technically advanced material, to suit their particular needs.

      Statistics are everywhere, as integral to science as they are to business, and in the popular media hundreds of times a day. In this age of big data, a basic grasp of statistical literacy is more important than ever if we want to separate the fact from the fiction, the ostentatious embellishments from the raw evidence -- and even more so if we hope to participate in the future, rather than being simple bystanders. In The Art of Statistics, world-renowned statistician David Spiegelhalter shows readers how to derive knowledge from raw data by focusing on the concepts and connections behind the math. Drawing on real world examples to introduce complex issues, he shows us how statistics can help us determine the luckiest passenger on the Titanic, whether a notorious serial killer could have been caught earlier, and if screening for ovarian cancer is beneficial. The Art of Statistics not only shows us how mathematicians have used statistical science to solve these problems -- it teaches us how we too can think like statisticians. We learn how to clarify our questions, assumptions, and expectations when approaching a problem, and -- perhaps even more importantly -- we learn how to responsibly interpret the answers we receive. Combining the incomparable insight of an expert with the playful enthusiasm of an aficionado, The Art of Statistics is the definitive guide to stats that every modern person needs.

    Stay in the know, spot trends as they happen, and push your business to new limits. This e-book introduces Microsoft Power BI basics through a practical, scenario-based guided tour of the tool, showing you how to build analytical solutions using Power BI. Get an overview of Power BI, or dig deeper and follow along on your PC using the book's examples.

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     If you have ever found yourself lost halfway through other introductory materials on this topic, this is the book for you. If you don't understand set terminology such as vectors, hyperplanes, and centroids, then this is also the book for you. This starter course isn't a picture story book but does include many visual examples that break algorithms down into a digestible and practical format. As a starter course, this book connects the dots and offers the crash course I wish I had when I first started. The kind of guide I wish had before I started taking on introductory courses that presume you’re two days away from an advanced mathematics exam. That’s why this introductory course doesn’t go further on the subject than other introductory books, but rather, goes a step back. A half-step back in order to help everyone make his or her first strides in machine learning and is an ideal study companion for the visual learner. In this step-by-step guide you will learn: - How to download free datasets - What tools and software packages you need - Data scrubbing techniques, including one-hot encoding, binning and dealing with missing data - Preparing data for analysis, including k-fold Validation - Regression analysis to create trend lines - Clustering, including k-means and k-nearest Neighbors - Naive Bayes Classifier to predict new classes - Anomaly detection and SVM algorithms to combat anomalies and outliers - The basics of Neural Networks - Bias/Variance to improve your machine learning model - Decision Trees to decode classification Please feel welcome to join this starter course by buying a copy, or sending a free sample to your preferred device.

    In the Mastering Emacs ebook you will learn the answers to all the concepts that take weeks, months or even years to truly learn, all in one place.“Emacs is such a hard editor to learn”But why is it so hard to learn? As it turns out, it's almost always the same handful of issues that everyone faces.If you have tried to learn Emacs you will have struggled with the same problems everyone faces, and few tutorials to see you through it.I have dedicated the first half of the book to explaining the essence of Emacs — and in doing so, how to overcome these issues:Memorizing Emacs’s keys: You will learn Emacs one key at a time, starting with the arrow keys. To feel productive in Emacs, it’s important you start on an equal footing — without too many new concepts and keys to memorize. Each chapter will introduce more keys and concepts so you can learn at your own pace. Discovering new modes and features: Emacs is a self-documenting editor, and I will teach you how to use the apropos, info, and describe system to discover new modes and features, or help you find things you forgot! Customizing Emacs: You don’t have to learn Emacs Lisp to alter a lot of Emacs’s functionality. Most changes you want to make are possible using Emacs’s Customize interface and I will show you how to use it efficiently. Understanding the terminology: Emacs is so old it predates almost every other editor and all modern user interfaces. I have an entire chapter dedicated to the unique terminology in Emacs; how it is different from other editors, and what that means to you.

    Full of insights, arguments and philosophical perspectives, the book covers an amazing array of topics. Beginning in antiquity with Democritus, it progresses through logic and set theory, computability and complexity theory, quantum computing, cryptography, the information content of quantum states and the interpretation of quantum mechanics. There are also extended discussions about time travel, Newcomb's Paradox, the anthropic principle and the views of Roger Penrose. Aaronson's informal style makes this fascinating book accessible to readers with scientific backgrounds, as well as students and researchers working in physics, computer science, mathematics and philosophy.

    This guide introduces new features and capabilities, providing a practical, high-level overview for IT professionals ready to begin deployment planning now. This book is a preview, a work in progress about a work in progress. It offers a snapshot of the Windows 10 Technical Preview as of April 2015, on the eve of the BUILD Developers’ Conference in San Francisco.