MACHINE LEARNING AN ALGORITHMIC PERSPECTIVE EBOOK
Editorial Reviews. Review. "I thought the first edition was hands down, one of the best texts An Algorithmic Perspective, Second Edition (Chapman & Hall/Crc Machine Learning & Pattern Recognition) eBook: Stephen Marsland: Kindle Store. MACHINE LEARNING: An Algorithmic Perspective, Second Edition. Stephen International Standard Book Number (eBook - PDF). Machine Learning & Pattern Recognition Series. Stephen Marsland. A CHAP MAN & HALL BOOK. Page 2. Machine. Learning. An Algorithmic. Perspective.
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Get this from a library! Machine Learning: an algorithmic perspective. [Stephen Marshland]. exigo.pro-mscs-sem1/CS/Textbook/CSTxtBook-Stephen Marsland- Machine Learning- An Algorithmic Perspective, Second Edition-Chapman and. Traditional books on machine learning can be divided into two groups- those aimed at advanced undergraduates or early postgraduates with.
The book will also be useful to professionals who can quickly inform and refresh their memory and knowledge of how machine learning works and what are the fundamental approaches and methods used in this area.
As a whole, it provides an essential source for machine learning methodologies and techniques, how they work, and what are their application areas. It includes a basic primer on Python and has an accompanying website.
It has excellent breadth and is comprehensive in terms of the topics it covers, both in terms of methods and in terms of concepts and theory.
It would be excellent as a first exposure to the subject, and would put the various ideas in context …" —David J. Hand, International Statistical Review , 78 "If you are interested in learning enough AI to understand the sort of new techniques being introduced into Web 2 applications, then this is a good place to start.
Overall it works and much of the mathematics is explained in ways that make it fairly clear what is going on …. This is a suitable introduction to AI if you are studying the subject on your own and it would make a good course text for an introduction and overview of AI. 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.
Machine Learning : an algorithmic perspective
Unsupervised Learning. Dimensionality Reduction. Optimization and Search.
Drawing from computer science, statistics, mathematics, and engineering, the multidisciplinary nature of machine learning is underscored by its applicability to areas ranging from finance to biology and medicine to physics and chemistry. Written in an easily accessible style, this book bridges the gaps between disciplines, providing the ideal blend of theory and practical, applicable knowledge.
PDF Machine Learning: An Algorithmic Perspective (Chapman & Hall/Crc Machine Learning & Pattern
Clemitson has worked in the chemical industry for 45 years. Predominantly, he worked in the polymer industry, both in production and development, concentrating on rubbers and polyurethanes.
In the concluding years of his full-time work, he was employed in the development and manufacture of polyurethane elastomers and foams. He also gave lectures at the local training institute and to industry on aspects of polyurethane and rubber technology.
He has authored two books on polyurethane elastomers, namely Castable Polyurethane Elastomers and Polyurethane Casting Primer. An Algorithmic Perspective. Stephen Marsland.
Theory Backed up by Practical Examples The book covers neural networks, graphical models, reinforcement learning, evolutionary algorithms, dimensionality reduction methods, and the important area of optimization.Please re-enter recipient e-mail address es. Unsupervised Learning.
The author uses data from a variety of applications to demonstrate the methods and includes practical problems for students to solve.
Dimensionality Reduction. Reviews Editorial reviews. Optimization and Search.
Unfortunately, computer science students without a strong statistical background often find it hard to get started in this area. Don't have an account?
The author addresses the topics in a practical way while providing complete information and references where other expositions can be found. Please be aware that the delivery time frame may vary according to the area of delivery - the approximate delivery time is usually between business days.