of Toronto and Google), Rodney Brooks (Rethink Robotics), Yann LeCun (Facebook) , Fei-Fei Li (Stanford and Google), Yoshua Bengio (Univ. of Montreal), Andrew Ng (AI Fund), Daphne Koller (Stanford), Stuart Russell (UC Berkeley), Nick Bostrom (Univ. of Oxford), Barbara Grosz (Harvard), David Ferrucci (Elemental Cognition), James Manyika (McKinsey), Judea Pearl (UCLA), Josh Tenenbaum (MIT), Rana el Kaliouby (Affectiva), Daniela Rus (MIT), Jeff Dean (Google), Cynthia Breazeal (MIT), Oren Etzioni (Allen Institute for AI), Gary Marcus (NYU), and Bryan Johnson (Kernel).Martin Ford is a prominent futurist, and author of Financial Times Business Book of the Year, Rise of the Robots. He speaks at conferences and companies around the world on what AI and automation might mean for the future. Editorial reviews: "In his newest book, Architects of Intelligence, Martin Ford provides us with an invaluable opportunity to learn from some of the most prominent thought leaders about the emerging fields of science that are shaping our future." -Al Gore, Former Vice President of the US "AI is going to shape our future, and Architects of Intelligence offers a unique and fascinating collection of perspectives from the top researchers and entrepreneurs who are driving progress in the field." - Eric Schmidt, former Chairman and CEO, Google "The best way to understand the challenges and consequences of AGI is to see inside the minds of industry experts shaping the field. Architects of Intelligence gives you that power." -Sam Altman, President of Y Combinator and co-chairman of OpenAI "Architects of Intelligence gets you inside the minds of the people building the technology that is going to transform our world. This is a book that everyone should read." -Reid Hoffman, Co-founder of LinkedIn

    It is a great book, not just for beginning programmers, but also for computer users who would want to have an idea what is happening behind the scenes as they work with various computer programs. In this book, you are going to learn what the C programming language entails, how to write conditions, expressions, statements and even commands, for the language to perform its functions efficiently. You will learn too how to organize relevant expressions so that after compilation and execution, the computer returns useful results and not error messages. Additionally, this book details the data types that you need for the C language and how to present it as well. Simply put, this is a book for programmers, learners taking other computer courses, and other computer users who would like to be versed with the workings of the most popular computer language, C. In this book You'll learn: What Is The C Language? Setting Up Your Local Environment The C Structure and Data Type C Constants and Literals C Storage Classes Making Decisions In C The Role Of Loops In C Programming Functions in C Programming Structures and Union in C Bit Fields and Typedef Within C. C Header Files and Type Casting Benefits Of Using The C Language ...and much more!! Download your copy today! click the BUY button and download it right now!

    In the next ten years, change will happen even faster. As Hillary Clinton's Senior Advisor for Innovation, Alec Ross travelled nearly a million miles to forty-one countries, the equivalent of two round-trips to the moon. From refugee camps in the Congo and Syrian war zones, to visiting the world's most powerful people in business and government, Ross's travels amounted to a four-year masterclass in the changing nature of innovation. In The Industries of the Future, Ross distils his observations on the forces that are changing the world. He highlights the best opportunities for progress and explains how countries thrive or sputter. Ross examines the specific fields that will most shape our economic future over the next ten years, including robotics, artificial intelligence, the commercialization of genomics, cybercrime and the impact of digital technology. Blending storytelling and economic analysis, he answers questions on how we will need to adapt. Ross gives readers a vivid and informed perspective on how sweeping global trends are affecting the ways we live, now and tomorrow.

    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.

    As an AI researcher with 25 years of experience, professor Mike Wooldridge has learned to be obsessively cautious about such claims, while still promoting an intense optimism about the future of the field. There have been genuine scientific breakthroughs that have made AI systems possible in the past decade that the founders of the field would have hailed as miraculous. Driverless cars and automated translation tools are just two examples of AI technologies that have become a practical, everyday reality in the past few years, and which will have a huge impact on our world.While the dream of conscious machines remains, Professor Wooldridge believes, a distant prospect, the floodgates for AI have opened. Wooldridge's A Brief History of Artificial Intelligence is an exciting romp through the history of this groundbreaking field--a one-stop-shop for AI's past, present, and world-changing future.

    But building a machine learning system requires that you make practical decisions: Should you collect more training data? Should you use end-to-end deep learning? How do you deal with your training set not matching your test set? and many more. Historically, the only way to learn how to make these "strategy" decisions has been a multi-year apprenticeship in a graduate program or company. This is a book to help you quickly gain this skill, so that you can become better at building AI systems.

    With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. You’ll explore the basic operations and common functions of Spark’s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Spark’s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasets—Spark’s core APIs—through worked examples Dive into Spark’s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Spark’s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation

    Our inaugural effort is OpenIntro Statistics. Probability is optional, inference is key, and we feature real data whenever possible. Files for the entire book are freely available at openintro.org, and anybody can purchase a paperback copy from amazon.com for under $10.The future for OpenIntro depends on the involvement and enthusiasm of our community. Visit our website, openintro.org. We provide free course management tools, including an online question bank, utilities for creating course quizzes, and many other helpful resources.CERTAIN CONTENT THAT APPEARS ON THIS SITE COMES FROM AMAZON SERVICES LLC. THIS CONTENT IS PROVIDED ‘AS IS’ AND IS SUBJECT TO CHANGE OR REMOVAL AT ANY TIME.Can’t find it here? Search Amazon.com Search: All Products Apparel & AccessoriesBabyBeautyBooksCamera & PhotoCell Phones & ServiceClassical MusicComputersComputer & Video GamesDVDElectronicsGourmet FoodHome & GardenMiscellaneousHealth & Personal CareJewelry & WatchesKitchen & HousewaresMagazine SubscriptionsMusicMusical InstrumentsSoftwareSports & OutdoorsTools & HardwareToys & GamesVHS Keywords:

    In How to Create a Mind, Kurzweil presents a provocative exploration of the most important project in human-machine civilization—reverse engineering the brain to understand precisely how it works and using that knowledge to create even more intelligent machines.Kurzweil discusses how the brain functions, how the mind emerges from the brain, and the implications of vastly increasing the powers of our intelligence in addressing the world’s problems. He thoughtfully examines emotional and moral intelligence and the origins of consciousness and envisions the radical possibilities of our merging with the intelligent technology we are creating.Certain to be one of the most widely discussed and debated science books of the year, How to Create a Mind is sure to take its place alongside Kurzweil’s previous classics which include Fantastic Voyage: Live Long Enough to Live Forever and The Age of Spiritual Machines.

    This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

      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.

    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)

    Not only are all of our business, scientific, and government transactions now computerized, but the widespread use of digital cameras, publication tools, and bar codes also generate data. On the collection side, scanned text and image platforms, satellite remote sensing systems, and the World Wide Web have flooded us with a tremendous amount of data. This explosive growth has generated an even more urgent need for new techniques and automated tools that can help us transform this data into useful information and knowledge.Like the first edition, voted the most popular data mining book by KD Nuggets readers, this book explores concepts and techniques for the discovery of patterns hidden in large data sets, focusing on issues relating to their feasibility, usefulness, effectiveness, and scalability. However, since the publication of the first edition, great progress has been made in the development of new data mining methods, systems, and applications. This new edition substantially enhances the first edition, and new chapters have been added to address recent developments on mining complex types of data- including stream data, sequence data, graph structured data, social network data, and multi-relational data.A comprehensive, practical look at the concepts and techniques you need to know to get the most out of real business dataUpdates that incorporate input from readers, changes in the field, and more material on statistics and machine learningDozens of algorithms and implementation examples, all in easily understood pseudo-code and suitable for use in real-world, large-scale data mining projectsComplete classroom support for instructors at www.mkp.com/datamining2e companion site

    You will use it from high school to college and beyond. The full version is absolutely FREE. Features Conversion of over 1,000 units. Metric, English, and US customary systems. Length, Area, Volume, Speed, Force, Energy, Electricity, Viscosity, Temperature, and more. List of powers of 10 prefixes. Explanation of SI writing style. Approximate conversion of units. Clear and concise explanations. Difficult concepts are explained in simple terms. Navigate from Table of Contents or search for words or phrases. Add bookmarks and annotation. Access the guide anytime, anywhere - at home, on the train, in the subway. Use your down time to prepare for an exam. Always have the guide available for a quick reference. Indispensable resource for technical and life science students. The full version is absolutely FREE. FREE updates. Table of Contents Conversion of units: Length: Definition | Conversion Area: Definition | 2-D Formulae | 3-D Formulae | Conversion Volume: Definition | Formulae | Conversion Angle: Definition | Conversion Mass: Definition | Conversion Time: Definition | Conversion Speed: Definition | Conversion Acceleration: Definition | Conversion Force: Definition | Conversion Pressure or mechanical stress: Definition | Conversion Energy, work, or heat: Definition | Conversion Power: Definition | Conversion Angular momentum: Definition | Conversion Electricity: Current | Charge | Resistance | Voltage | Formulae | Conversion Viscosity: Definition | Conversion Information entropy: Definition | Conversion Temperature: Definition | Conversion Approximate conversion of units History: Systems of measurement | History of measurement Metric system (SI): Definition | SI writing style | Powers of 10 prefixes Other Systems: English system | Imperial unit | United States customary units | Comparison of the Imperial and U.S. customary systems

    For centuries, the power of zero savored of the demonic; once harnessed, it became the most important tool in mathematics. Zero follows this number from its birth as an Eastern philosophical concept to its struggle for acceptance in Europe and its apotheosis as the mystery of the black hole. Today, zero lies at the heart of one of the biggest scientific controversies of all time, the quest for the theory of everything. Elegant, witty, and enlightening, Zero is a compelling look at the strangest number in the universe and one of the greatest paradoxes of human thought.