**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

**Machine Learning and Data Mining: Lecture Notes**

by

**Aaron Hertzmann**-

**University of Toronto**

Contents: Introduction to Machine Learning; Linear Regression; Nonlinear Regression; Quadratics; Basic Probability Theory; Probability Density Functions; Estimation; Classification; Gradient Descent; Cross Validation; Bayesian Methods; and more.

(

**3961**views)

**Machine Learning for Data Streams**

by

**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.

(

**486**views)

**Introduction to Machine Learning**

by

**Alex Smola, S.V.N. Vishwanathan**-

**Cambridge University Press**

Over the past two decades Machine Learning has become one of the mainstays of information technology and a rather central part of our life. Smart data analysis will become even more pervasive as a necessary ingredient for technological progress.

(

**2962**views)

**Practical Artificial Intelligence Programming in Java**

by

**Mark Watson**-

**Lulu.com**

The book uses the author's libraries and the best of open source software to introduce AI (Artificial Intelligence) technologies like neural networks, genetic algorithms, expert systems, machine learning, and NLP (natural language processing).

(

**15245**views)