Machine Learning : an algorithmic perspective

✍ Scribed by Marshland, Stephen

Publisher: CRC Press
Year: 2015
Tongue: English
Leaves: 452
Series: Chapman & Hall/CRC machine learning & pattern recognition series
Edition: 2ed.
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Introduction. Linear Discriminants. The Multi-Layer Perceptron. Radial Basis Functions and Splines. Support Vector Machines. Learning with Trees. Decision by Committee: Ensemble Learning. Probability and Learning. Unsupervised Learning. Dimensionality Reduction. Optimization and Search. Evolutionary Learning. Reinforcement Learning. Markov Chain Monte Carlo (MCMC) Methods. Graphical Models. Python.

Abstract:

Covers neural networks, graphical models, reinforcement learning, evolutionary algorithms, dimensionality reduction methods, and the important area of optimization. This book includes examples based Read more...

✦ Table of Contents

Content: Introduction --
Preliminaries --
Neurons, neural networks, and linear discriminants --
The multi-layer perceptron --
Radial basis functions and splines --
Dimensionality reduction --
Probabilistic learning --
Support vector machines --
Optimisation and search --
Evolutionary learning --
Reinforcement learning --
Learning with trees --
Decision by committee: ensemble learning --
Unsupervised learning --
Markov chain Monte Carlo (MCMC) methods --
Graphical models --
Symmetric weights and deep belief networks --
Gaussian processes --
Python.

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