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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.
This clear, well illustrated text takes the reader through the basics of film analysis, drawing on a wide range of film for discussion. Questions of genre and the contexts and meanings of film are considered.
This comprehensive book provides a well-rounded introduction to Israel—a definitive account of the nation's past, its often controversial present, and much more. Written by a leading historian of the Middle East, Israel is organized around six major themes: land and people, history, society, politics, economics, and culture. The only available volume to offer such a complete account, this book is written for general readers and students who may have little background knowledge of this nation or its rich culture. Based on research by scholars with extensive firsthand knowledge of Israel, this book offers accessible, clearly explained material, enhanced with a generous selection of images, maps, charts, tables, graphs, and sidebars. This book provides readers with a solid foundation of knowledge about Israel and provides useful reference lists by topic for those inspired to read further.
When the Book of Abraham was first published to the world in 1842, it was published as "a translation of some ancient records that have fallen into [Joseph Smith's] hands from the catacombs of Egypt, purporting to be the writings of Abraham while he was in Egypt, called 'The Book of Abraham, Written by his Own Hand, upon Papyrus.'" The resultant record was thus connected with the papyri once owned by Joseph Smith, though which papyrus of the four or five in his possession was never specified. Those papyri would likely interest only a few specialists--were the papyri not bound up in a religious controversy. This controversy covers a number of interrelated issues, and an even greater number of theories have been put forward about these issues. Given the amount of information available, the various theories, and the variety of fields of study the subject requires, misunderstandings and misinformation often prevail. The goal with the Introduction to the Book of Abraham is to make reliable information about the Book of Abraham accessible to the general reader.
Employing a practical, "learn by doing" approach, this first-rate text fosters the development of the skills beyond the pure mathematics needed to set up and manipulate mathematical models. The author draws on a diversity of fields — including science, engineering, and operations research — to provide over 100 reality-based examples. Students learn from the examples by applying mathematical methods to formulate, analyze, and criticize models. Extensive documentation, consisting of over 150 references, supplements the models, encouraging further research on models of particular interest. The lively and accessible text requires only minimal scientific background. Designed for senior college or beginning graduate-level students, it assumes only elementary calculus and basic probability theory for the first part, and ordinary differential equations and continuous probability for the second section. All problems require students to study and create models, encouraging their active participation rather than a mechanical approach. Beyond the classroom, this volume will prove interesting and rewarding to anyone concerned with the development of mathematical models or the application of modeling to problem solving in a wide array of applications.
This new edition of The Caucasus is a thorough update of an essential guide that has introduced thousands of readers to a complex region. Armenia, Azerbaijan, Georgia and the break-away territories that have tried to split away from them constitute one of the most diverse and challenging regions on earth, impressing the visitor with their multi-layered history and ethnic complexity. Over the last few years, the South Caucasus region has captured international attention again because of disputes between the West and Russia, its unresolved conflicts, and its role as an energy transport corridor to Europe. The Caucasus gives the reader a historical overview and an authoritative guide to the three conflicts that have blighted the region. Thomas de Waal tells the story of the "Five-Day War" between Georgia and Russia and recent political upheavals in all three countries. He also finds time to tell the reader about Georgian wine, Baku jazz and how the coast of Abkhazia was known as "Soviet Florida." Short, stimulating and rich in detail, The Caucasus is the perfect guide to this fascinating and little-understood region.
Heidegger is a classic introduction to Heidegger's notoriously difficult work. Truly accessible, it combines clarity of exposition with an authoritative handling of the subject-matter. Richard Polt has written a work that will become the standard text for students looking to understand one of the century's greatest minds.