This is a comprehensive introduction to books and print culture which examines the move from the spoken word to written texts, the book as commodity, the power and profile of readers, and the future of the book in an electronic age.

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.

A comprehensive and accessible introduction to all aspects of decision theory, now with new and updated discussions and over 140 exercises.

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.

This concise book presents theory and teaches skills allowing students from all academic backgrounds to understand the communication field.