Stephen Marsland

Machine Learning (eBook, PDF)

An Algorithmic Perspective

• Format: PDF

Produktbeschreibung

Traditional books on machine learning can be divided into two groups- those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 406
• Erscheinungstermin: 23. März 2011
• Englisch
• ISBN-13: 9781420067194
• Artikelnr.: 55340422

Autorenporträt

Stephen Marsland is a professor of scientific computing and the postgraduate director of the School of Engineering and Advanced Technology (SEAT) at Massey University. His research interests in mathematical computing include shape spaces, Euler equations, machine learning, and algorithms. He received a PhD from Manchester University

Inhaltsangabe

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.