Machine Learning

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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 also provides the background needed to understand how and why these algorithms work. Machine Learning: An Algorithmic Perspective is that text.

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. It treads the fine line between adequate academic rigor and overwhelming students with equations and mathematical concepts. The author addresses the topics in a practical way while providing complete information and references where other expositions can be found. He includes examples based on widely available datasets and practical and theoretical problems to test understanding and application of the material. The book describes algorithms with code examples backed up by a website that provides working implementations in Python. The author uses data from a variety of applications to demonstrate the methods and includes practical problems for students to solve.

Highlights a Range of Disciplines and Applications

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.

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Python Machine Learning


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Author by : Sebastian Raschka
Languange Used : en
Release Date : 2015-09-23
Publisher by : Packt Publishing Ltd

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About T

Machine Learning


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Author by : Ethem Alpaydin
Languange Used : en
Release Date : 2016-10-07
Publisher by : MIT Press

A concise overview of machine learning -- computer programs that learn from data -- which underlies applicatio

Machine Learning


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Author by : R.S. Michalski
Languange Used : en
Release Date : 2013-04-17
Publisher by : Springer Science & Business Media

The ability to learn is one of the most fundamental attributes of intelligent behavior. Consequently, progress

Introduction To Machine Learning


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Author by : Ethem Alpaydin
Languange Used : en
Release Date : 2014-08-29
Publisher by : MIT Press

The goal of machine learning is to program computers to use example data or past experience to solve a given p

Machine Learning


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Author by : Tom Michael Mitchell
Languange Used : en
Release Date : 1997-03-01
Publisher by : McGraw-Hill Science/Engineering/Math

Mitchell covers the field of machine learning, the study of algorithms that allow computer programs to automat

Elements Of Machine Learning


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Author by : Pat Langley
Languange Used : en
Release Date : 1996
Publisher by : Morgan Kaufmann

Machine learning is the computational study of algorithms that improve performance based on experience, and th

Machine Learning For Audio Image And Video Analysis


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Author by : Francesco Camastra
Languange Used : en
Release Date : 2015-07-21
Publisher by : Springer

This second edition focuses on audio, image and video data, the three main types of input that machines deal w

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