**Lecture Notes in Machine Learning**

by Zdravko Markov

**Publisher**: Central Connecticut State University 2003**Number of pages**: 65

**Description**:

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.

Download or read it online for free here:

**Download link**

(340KB, PDF)

## Similar books

**Information Theory, Inference, and Learning Algorithms**

by

**David J. C. MacKay**-

**Cambridge University Press**

A textbook on information theory, Bayesian inference and learning algorithms, useful for undergraduates and postgraduates students, and as a reference for researchers. Essential reading for students of electrical engineering and computer science.

(

**12414**views)

**Machine Learning**

by

**Abdelhamid Mellouk, Abdennacer Chebira**-

**InTech**

Neural machine learning approaches, Hamiltonian neural networks, similarity discriminant analysis, machine learning methods for spoken dialogue simulation and optimization, linear subspace learning for facial expression analysis, and more.

(

**8982**views)

**Reinforcement Learning**

by

**C. Weber, M. Elshaw, N. M. Mayer**-

**InTech**

This book describes and extends the scope of reinforcement learning. It also shows that there is already wide usage in numerous fields. Reinforcement learning can tackle control tasks that are too complex for traditional controllers.

(

**11525**views)

**Introduction to Machine Learning**

by

**Amnon Shashua**-

**arXiv**

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).

(

**13013**views)