Introduction to Machine Learning
by Amnon Shashua
Publisher: arXiv 2009
Number of pages: 109
Description:
Introduction to Machine learning covering Statistical Inference (Bayes, EM, ML/MaxEnt duality), algebraic and spectral methods (PCA, LDA, CCA, Clustering), and PAC learning (the Formal model, VC dimension, Double Sampling theorem).
Download or read it online for free here:
Download link
(680KB, PDF)
Similar books
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.
(14986 views)
Machine Learning, Neural and Statistical Classificationby D. Michie, D. J. Spiegelhalter - Ellis Horwood
The book provides a review of different approaches to classification, compares their performance on challenging data-sets, and draws conclusions on their applicability to realistic industrial problems. A wide variety of approaches has been taken.
(13942 views)
A First Encounter with Machine Learningby Max Welling - University of California Irvine
The book you see before you is meant for those starting out in the field of machine learning, who need a simple, intuitive explanation of some of the most useful algorithms that our field has to offer. A prelude to the more advanced text books.
(3590 views)
Lecture Notes in Machine Learningby Zdravko Markov - Central Connecticut State University
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 ...
(3674 views)