Machine Learning Books - Free eBooks Directory
Free Machine Learning ebooks. Categorized directory of free Machine Learning books. Read online or download free eBooks in different formats.
Free eBooks
49
Ebook Details
Author
Max Welling
Publisher
University of California Irvine 2011
Description: The book you see before you is meant for those starting out in the field of machine learning.
Free eBooks
50
Ebook Details
Author
David Barber
Publisher
Cambridge University Press 2011
Free eBooks
46
Ebook Details
Author
Amnon Shashua
Publisher
arXiv 2009
Free eBooks
52
Ebook Details
Author
C. Weber, M. Elshaw, N. M. Mayer
Publisher
InTech 2008
The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields.
Free eBooks
59
Ebook Details
Author
Gianluca Bontempi, Souhaib Ben Taieb
Publisher
2017
This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data. In particular, we focus on supervised learning problems.
Free eBooks
72
Ebook Details
Author
Alexander Rakhlin, Karthik Sridharan
Publisher
University of Pennsylvania 2014
This course will focus on theoretical aspects of Statistical Learning and Sequential Prediction. The minimax approach, which we emphasize throughout the course, offers a systematic way of comparing learning problems.
Free eBooks
51
Ebook Details
Author
Abdelhamid Mellouk, Abdennacer Chebira
Publisher
InTech 2009
Neural machine learning approaches, Hamiltonian neural networks, similarity discriminant analysis, machine learning methods for spoken dialogue simulation and optimization,
Free eBooks
44
Ebook Details
Author
Shai Shalev-Shwartz, Shai Ben-David
Publisher
Cambridge University Press 2014
Free eBooks
51
Ebook Details
Author
LISA lab
Publisher
University of Montreal 2015
Free eBooks
47
Ebook Details
Author
Zdravko Markov
Publisher
Central Connecticut State University 2003
Contents: Introduction; Concept learning; Languages for learning; Version space learning; Induction of Decision trees; Covering strategies; Searching the generalization / specialization graph; Inductive Logic Progrogramming; Unsupervised Learning; Explanation-based Learning.