book review


Free Book: Statistics -- New Foundations, Toolbox, and Machine Learning Recipes

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This book is intended for busy professionals working with data of any kind: engineers, BI analysts, statisticians, operations research, AI and machine learning professionals, economists, data scientists, biologists, and quants, ranging from beginners to executives. In about 300 pages and 28 chapters it covers many new topics, offering a fresh perspective on the subject, including rules of thumb and recipes that are easy to automate or integrate in black-box systems, as well as new model-free, data-driven foundations to statistical science and predictive analytics. The approach focuses on robust techniques; it is bottom-up (from applications to theory), in contrast to the traditional top-down approach. The material is accessible to practitioners with a one-year college-level exposure to statistics and probability. The compact and tutorial style, featuring many applications with numerous illustrations, is aimed at practitioners, researchers, and executives in various quantitative fields.


Opinion 'There's Just No Doubt That It Will Change the World': David Chalmers on V.R. and A.I.

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Over the past two decades, the philosopher David Chalmers has established himself as a leading thinker on consciousness. He began his academic career in mathematics but slowly migrated toward cognitive science and philosophy of mind. He eventually landed at Indiana University working under the guidance of Douglas Hofstadter, whose influential book "Gödel, Escher, Bach: An Eternal Golden Braid" had earned him a Pulitzer Prize. Chalmers's dissertation, "Toward a Theory of Consciousness," grew into his first book, "The Conscious Mind" (1996), which helped revive the philosophical conversation on consciousness. Perhaps his best-known contribution to philosophy is "the hard problem of consciousness" -- the problem of explaining subjective experience, the inner movie playing in every human mind, which in Chalmers's words will "persist even when the performance of all the relevant functions is explained."


Top 10 Books on Artificial Intelligence You Cannot Afford to Miss Analytics Insight

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Artificial Intelligence is the need of the hour. This technology of today is neither an elementary school math nor a rocket science application. The understanding of AI not only allows business decision makers and enthusiasts to make advancements in technologies but also let them make processes better. Another term that is doing the rounds is artificial general intelligence (AGI) which encompasses human-level cognitive ability making automation think and work like a human mind. So how do you benefit from AI and the latest advancements that move around it?


Top AI Books for Summer Reading in 2019 - AI Trends

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The recommended AI books on the list of published by MarkTechPost is selected on the basis of their reviews on Amazon, social media influence, popularity and online mentions in AI domains. This is not meant to be a ranking. A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. In this mind-expanding book, scientific pioneer Marvin Minsky continues his groundbreaking research, offering a fascinating new model for how our minds work.


Artificial Intelligence Changes Everything in the Security Industry

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During my years at Dell, we would share what we serendipitously found in the way of a good read. I thought I'd continue that practice, sending your way, if you haven't already discovered it, Kai-Fu Lee's book AI Superpowers: China, Silicon Valley, and the New World Order. It's a fascinating read – particularly his insight that, "AI will be to the 21st Century what electricity was to the last…and Data – the oil that drives the generator." Just as nineteenth-century entrepreneurs applied the electricity break-through to cooking food, lighting rooms and powering industrial equipment, today's AI entrepreneurs are doing the same with the deep learning of artificial narrow intelligence (ANI). Lee's insights were incisive and inspiring – a clarion call of caution mixed with an articulate voice of hope and encouragement.


Got Any Time-Travel Plans This Summer?

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The last few years have seen an uptick in pop culture stories featuring time travel, from the repetitions and revisions of "The Good Place" and "Russian Doll" to developments in "Game of Thrones," "Star Trek: Discovery" and "Avengers: Endgame." Sometimes the MacGuffin by which we get to play with anachronism, but often also rooted in questions of free will and determinism, time travel is a fascinating springboard for fiction: Are there many futures, or just one? Can you change the past without changing the future, or yourself? This column brings together books about time fractured and out of joint, time as an unbroken lineage resisting empire, and time travel glimpsed through the overlapping lenses of psychology, philosophy and physics. Kameron Hurley's THE LIGHT BRIGADE (Saga, $26.99) is based on her 2015 short story of the same name, fleshing out the high-concept skeleton of a story about soldiers who are literally broken into light in order to teleport them to different theaters of war.


Preventing Disparities: Bayesian and Frequentist Methods for Assessing Fairness in Machine-Learning Decision-Support Models IntechOpen

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The first chapter is the Introductory chapter. The second chapter aims to provide an update of the recent advances in the field of rational design of PDE inhibitors. The third chapter includes designing a series of peptidic inhibitors that possessed a substrate transition-state analog and evaluating the structure-activity relationship of the designed inhibitors, based on docking and scoring, using the docking simulation software Molecular Operating Environment. The aim of the forth chapter is to develop structure-property relationships for the qualitative and quantitative prediction of the reverse-phase liquid chromatographic retention times of chlorogenic acids.


Top Artificial Intelligence Books to Read in 2019 MarkTechPost

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A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. In this mind-expanding book, scientific pioneer Marvin Minsky continues his groundbreaking research, offering a fascinating new model for how our minds work. He argues persuasively that emotions, intuitions, and feelings are not distinct things, but different ways of thinking. Introduction to Artificial Intelligence presents an introduction to the science of reasoning processes in computers, and the research approaches and results of the past two decades.


New Advances in Machine Learning IntechOpen

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The purpose of this book is to provide an up-to-date and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call "learning" tasks, as we use the word in daily life. It is also broad enough to encompass computers that improve from experience in quite straightforward ways. The book will be ... The purpose of this book is to provide an up-to-date and systematical introduction to the principles and algorithms of machine learning. The definition of learning is broad enough to include most tasks that we commonly call "learning" tasks, as we use the word in daily life.


Introduction to Multi-Armed Bandits

arXiv.org Artificial Intelligence

Multi-armed bandits a simple but very powerful framework for algorithms that make decisions over time under uncertainty. An enormous body of work has accumulated over the years, covered in several books and surveys. This book provides a more introductory, textbook-like treatment of the subject. Each chapter tackles a particular line of work, providing a self-contained, teachable technical introduction and a review of the more advanced results. The chapters are as follows: Stochastic bandits; Lower bounds; Bayesian Bandits and Thompson Sampling; Lipschitz Bandits; Full Feedback and Adversarial Costs; Adversarial Bandits; Linear Costs and Semi-bandits; Contextual Bandits; Bandits and Zero-Sum Games; Bandits with Knapsacks; Incentivized Exploration and Connections to Mechanism Design.