Logo

The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Large book cover: The Elements of Statistical Learning: Data Mining, Inference, and Prediction

The Elements of Statistical Learning: Data Mining, Inference, and Prediction
by

Publisher: Springer
ISBN/ASIN: 0387848576
ISBN-13: 9780387848570
Number of pages: 764

Description:
This book is an attempt to bring together many of the important new ideas in learning, and explain them in a statistical framework. While some mathematical details are needed, the authors emphasize the methods and their conceptual underpinnings rather than their theoretical properties. This book will appeal not just to statisticians but also to researchers and practitioners in a wide variety of fields.

Home page url

Download or read it online for free here:
Download link
(8.2MB, PDF)

Similar books

Book cover: Introduction To Machine LearningIntroduction To Machine Learning
by
This book concentrates on the important ideas in machine learning, to give the reader sufficient preparation to make the extensive literature on machine learning accessible. The author surveys the important topics in machine learning circa 1996.
(17625 views)
Book cover: Algorithms for Reinforcement LearningAlgorithms for Reinforcement Learning
by - Morgan and Claypool Publishers
We focus on those algorithms of reinforcement learning that build on the theory of dynamic programming. We give a comprehensive catalog of learning problems, describe the core ideas, followed by the discussion of their properties and limitations.
(2655 views)
Book cover: Gaussian Processes for Machine LearningGaussian Processes for Machine Learning
by - The MIT Press
Gaussian processes provide a principled, practical, probabilistic approach to learning in kernel machines. The treatment is comprehensive and self-contained, targeted at researchers and students in machine learning and applied statistics.
(17896 views)
Book cover: Machine Learning for Data StreamsMachine Learning for Data Streams
by - The MIT Press
This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA, allowing readers to try out the techniques after reading the explanations.
(783 views)