A Course in Machine Learning
by Hal Daumé III
Publisher: ciml.info 2012
Number of pages: 189
Description:
CIML is a set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.). It's focus is on broad applications with a rigorous backbone.
Download or read it online for free here:
Download link
(2.9MB, PDF)
Similar books
A Brief Introduction to Machine Learning for Engineersby Osvaldo Simeone - arXiv.org
This monograph provides the starting point to the literature that every engineer new to machine learning needs. It offers a basic and compact reference that describes key ideas and principles in simple terms and within a unified treatment.
(9503 views)
The Elements of Statistical Learning: Data Mining, Inference, and Predictionby T. Hastie, R. Tibshirani, J. Friedman - Springer
This book brings together many of the important new ideas in learning, and explains them in a statistical framework. The authors emphasize the methods and their conceptual underpinnings rather than their theoretical properties.
(44722 views)
Machine Learning for Data Streamsby Albert Bifet, et al. - 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.
(9310 views)
Introduction To Machine Learningby Nils J Nilsson
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.
(33613 views)