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Edition (Chapman & Hall/Crc Machine Learning & Pattern
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Machine Learning: An Algorithmic Perspective, Second
Edition (Chapman & Hall/Crc Machine Learning & Pattern
Recognition)
BOOK DETAIL
File Size: 23957 KB Print Length: 457 pages Publisher: Chapman and Hall/CRC; 2 edition (October 8,
2014) Publication Date: October 8, 2014 Sold by: Amazon.com Services LLC Language: English ASIN:
B00OGLE56Y Text-to-Speech: Not enabled
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Book Description
A Proven, Hands-On Approach for Students without a Strong Statistical Foundation Since the
best-selling first edition was published, there have been several prominent developments in the
field of machine learning, including the increasing work on the statistical interpretations of
machine learning algorithms. Unfortunately, computer science students without a strong statistical
background often find it hard to get started in this area. Remedying this deficiency, Machine
Learning: An Algorithmic Perspective, Second Edition helps students understand the algorithms
of machine learning. It puts them on a path toward mastering the relevant mathematics and
statistics as well as the necessary programming and experimentation. New to the Second Edition
Two new chapters on deep belief networks and Gaussian processes Reorganization of the chapters
to make a more natural flow of content Revision of the support vector machine material, including
a simple implementation for experiments New material on random forests, the perceptron
convergence theorem, accuracy methods, and conjugate gradient optimization for the multi-layer
perceptron Additional discussions of the Kalman and particle filters Improved code, including
better use of naming conventions in Python Suitable for both an introductory one-semester course
and more advanced courses, the text strongly encourages students to practice with the code. Each
chapter includes detailed examples along with further reading and problems. All of the code used
to create the examples is available on the author’s website.

TAGS Machine Learning: An Algorithmic Perspective, Second
Edition (Chapman & Hall/Crc Machine Learning & Pattern
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