Data Jujitsu: The Art of Turning Data into Product


D.J. Patil - 2012
    Acclaimed data scientist DJ Patil details a new approach to solving problems in Data Jujitsu.Learn how to use a problem's "weight" against itself to:Break down seemingly complex data problems into simplified partsUse alternative data analysis techniques to examine themUse human input, such as Mechanical Turk, and design tricks that enlist the help of your users to take short cuts around tough problemsLearn more about the problems before starting on the solutions—and use the findings to solve them, or determine whether the problems are worth solving at all.

Professional ASP.NET MVC 5


Jon Galloway - 2013
    Like previous versions, this guide shows you step-by-step techniques on using MVC to best advantage, with plenty of practical tutorials to illustrate the concepts. It covers controllers, views, and models; forms and HTML helpers; data annotation and validation; membership, authorization, and security.MVC 5, the latest version of MVC, adds sophisticated features such as single page applications, mobile optimization, and adaptive rendering A team of top Microsoft MVP experts, along with visionaries in the field, provide practical advice on basic and advanced MVC topics Covers controllers, views, models, forms, data annotations, authorization and security, Ajax, routing, ASP.NET web API, dependency injection, unit testing, real-world application, and much more Professional ASP.NET MVC 5 is the comprehensive resource you need to make the best use of the updated Model-View-Controller technology.

Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema


Lawrence Corr - 2011
    This book describes BEAM✲, an agile approach to dimensional modeling, for improving communication between data warehouse designers, BI stakeholders and the whole DW/BI development team. BEAM✲ provides tools and techniques that will encourage DW/BI designers and developers to move away from their keyboards and entity relationship based tools and model interactively with their colleagues. The result is everyone thinks dimensionally from the outset! Developers understand how to efficiently implement dimensional modeling solutions. Business stakeholders feel ownership of the data warehouse they have created, and can already imagine how they will use it to answer their business questions. Within this book, you will learn: ✲ Agile dimensional modeling using Business Event Analysis & Modeling (BEAM✲) ✲ Modelstorming: data modeling that is quicker, more inclusive, more productive, and frankly more fun! ✲ Telling dimensional data stories using the 7Ws (who, what, when, where, how many, why and how) ✲ Modeling by example not abstraction; using data story themes, not crow's feet, to describe detail ✲ Storyboarding the data warehouse to discover conformed dimensions and plan iterative development ✲ Visual modeling: sketching timelines, charts and grids to model complex process measurement - simply ✲ Agile design documentation: enhancing star schemas with BEAM✲ dimensional shorthand notation ✲ Solving difficult DW/BI performance and usability problems with proven dimensional design patterns Lawrence Corr is a data warehouse designer and educator. As Principal of DecisionOne Consulting, he helps clients to review and simplify their data warehouse designs, and advises vendors on visual data modeling techniques. He regularly teaches agile dimensional modeling courses worldwide and has taught dimensional DW/BI skills to thousands of students. Jim Stagnitto is a data warehouse and master data management architect specializing in the healthcare, financial services, and information service industries. He is the founder of the data warehousing and data mining consulting firm Llumino.

The Road to Conscious Machines: The Story of AI


Michael Wooldridge - 2020
    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.

AI: Its Nature and Future


Margaret A. Boden - 2016
    The results of Artificial Intelligence have been invaluable to biologists, psychologists, and linguists in helping to understand the processes of memory, learning, and language from a fresh angle. As a concept, Artificial Intelligence has fuelled and sharpened the philosophical debates concerning the nature of the mind, intelligence, and the uniqueness of human beings. Margaret A. Boden reviews the philosophical and technological challenges raised by Artificial Intelligence, considering whether programs could ever be really intelligent, creative or even conscious, and shows how the pursuit of Artificial Intelligence has helped us to appreciate how human and animal minds are possible.

Algorithms


Robert Sedgewick - 1983
    This book surveys the most important computer algorithms currently in use and provides a full treatment of data structures and algorithms for sorting, searching, graph processing, and string processing -- including fifty algorithms every programmer should know. In this edition, new Java implementations are written in an accessible modular programming style, where all of the code is exposed to the reader and ready to use.The algorithms in this book represent a body of knowledge developed over the last 50 years that has become indispensable, not just for professional programmers and computer science students but for any student with interests in science, mathematics, and engineering, not to mention students who use computation in the liberal arts.The companion web site, algs4.cs.princeton.edu contains An online synopsis Full Java implementations Test data Exercises and answers Dynamic visualizations Lecture slides Programming assignments with checklists Links to related material The MOOC related to this book is accessible via the "Online Course" link at algs4.cs.princeton.edu. The course offers more than 100 video lecture segments that are integrated with the text, extensive online assessments, and the large-scale discussion forums that have proven so valuable. Offered each fall and spring, this course regularly attracts tens of thousands of registrants.Robert Sedgewick and Kevin Wayne are developing a modern approach to disseminating knowledge that fully embraces technology, enabling people all around the world to discover new ways of learning and teaching. By integrating their textbook, online content, and MOOC, all at the state of the art, they have built a unique resource that greatly expands the breadth and depth of the educational experience.

Computing machinery and intelligence


Alan Turing - 1950
    The paper, published in 1950 in Mind, was the first to introduce his concept of what is now known as the Turing test to the general public.Published in Mind 49: page 433-460.(Source: Wikipedia)

What is a P-Value Anyway? 34 Stories to Help You Actually Understand Statistics


Andrew J. Vickers - 2009
    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.

Artificial Intelligence


Patrick Henry Winston - 1977
    From the book, you learn why the field is important, both as a branch of engineering and as a science. If you are a computer scientist or an engineer, you will enjoy the book, because it provides a cornucopia of new ideas for representing knowledge, using knowledge, and building practical systems. If you are a psychologist, biologist, linguist, or philosopher, you will enjoy the book because it provides an exciting computational perspective on the mystery of intelligence. The Knowledge You Need This completely rewritten and updated edition of Artificial Intelligence reflects the revolutionary progress made since the previous edition was published. Part I is about representing knowledge and about reasoning methods that make use of knowledge. The material covered includes the semantic-net family of representations, describe and match, generate and test, means-ends analysis, problem reduction, basic search, optimal search, adversarial search, rule chaining, the rete algorithm, frame inheritance, topological sorting, constraint propagation, logic, truth

The Linux Command Line


William E. Shotts Jr. - 2012
    Available here:readmeaway.com/download?i=1593279523The Linux Command Line, 2nd Edition: A Complete Introduction PDF by William ShottsRead The Linux Command Line, 2nd Edition: A Complete Introduction PDF from No Starch Press,William ShottsDownload William Shotts’s PDF E-book The Linux Command Line, 2nd Edition: A Complete Introduction

Doing Bayesian Data Analysis: A Tutorial Introduction with R and BUGS


John K. Kruschke - 2010
    Included are step-by-step instructions on how to carry out Bayesian data analyses.Download Link : readbux.com/download?i=0124058884            0124058884 Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan PDF by John Kruschke

Deep Learning


John D. Kelleher - 2019
    When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution.Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning—major trends, possible developments, and significant challenges.

Behind Deep Blue: Building the Computer That Defeated the World Chess Champion


Feng-Hsiung Hsu - 2002
    Written by the man who started the adventure, Behind Deep Blue reveals the inside story of what happened behind the scenes at the two historic Deep Blue vs. Kasparov matches. This is also the story behind the quest to create the mother of all chess machines. The book unveils how a modest student project eventually produced a multimillion dollar supercomputer, from the development of the scientific ideas through technical setbacks, rivalry in the race to develop the ultimate chess machine, and wild controversies to the final triumph over the world's greatest human player.In nontechnical, conversational prose, Feng-hsiung Hsu, the system architect of Deep Blue, tells us how he and a small team of fellow researchers forged ahead at IBM with a project they'd begun as students at Carnegie Mellon in the mid-1980s: the search for one of the oldest holy grails in artificial intelligence--a machine that could beat any human chess player in a bona fide match. Back in 1949 science had conceived the foundations of modern chess computers but not until almost fifty years later--until Deep Blue--would the quest be realized.Hsu refutes Kasparov's controversial claim that only human intervention could have allowed Deep Blue to make its decisive, "uncomputerlike" moves. In riveting detail he describes the heightening tension in this war of brains and nerves, the "smoldering fire" in Kasparov's eyes. Behind Deep Blue is not just another tale of man versus machine. This fascinating book tells us how man as genius was given an ultimate, unforgettable run for his mind, no, not by the genius of a computer, but of man as toolmaker.

Blockchain Revolution: How the Technology Behind Bitcoin Is Changing Money, Business, and the World


Don Tapscott - 2016
    But it is much more than that, too. It is a public ledger to which everyone has access, but which no single person controls. It allows for companies and individuals to collaborate with an unprecedented degree of trust and transparency. It is cryptographically secure, but fundamentally open. And soon it will be everywhere.In Blockchain Revolution, Don and Alex Tapscott reveal how this game-changing technology will shape the future of the world economy, dramatically improving everything from healthcare records to online voting, and from insurance claims to artist royalty payments. Brilliantly researched and highly accessible, this is the essential text on the next major paradigm shift. Read it, or be left behind.

Programming Game AI by Example


Mat Buckland - 2004
    Techniques covered include state- and goal-based behavior, inter-agent communication, individual and group steering behaviors, team AI, graph theory, search, path planning and optimization, triggers, scripting, scripted finite state machines, perceptual modeling, goal evaluation, goal arbitration, and fuzzy logic.