Introduction to Statistical Machine Learning
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Book Overview Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machin...
Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a powerful tool for analysing various kinds of data in many computer science/engineering areas including, image processing, speech processing, natural language processing, robot control, as well as in fundamental sciences such as biology, medicine, astronomy, physics, and materials.
Introduction to Statistical Machine Learning provides ageneral introduction to machine learning that covers a wide range of topics concisely and will help you bridge the gap between theory and practice. Part I discusses the fundamental concepts of statistics and probability that are used in describing machine learning algorithms. Part II and Part III explain the two major approaches of machine learning techniques; generative methods and discriminative methods. While Part III provides an in-depth look at advanced topics that play essential roles in making machine learning algorithms more useful in practice. The accompanying MATLAB/Octave programs provide you with the necessary practical skills needed to accomplish a wide range of data analysis tasks.
Book Details Format: Paperback | Pages: 534 | Language: English | Publisher: MORGAN KAUFMANN PUBL INC | ISBN: 0128021217
FormatPaperback
Pages534
LanguageEnglish
ISBN0128021217
EAN9780128021217
PublisherMORGAN KAUFMANN PUBL INC
Publication Date2015-09-25
Edition1
AccessoriesNo Accessory
ConditionNew
Product TypeQUALITY PAPERBACK BOOKS
Weight2.4 Pounds
Length9.2 Inches
Width7.5 Inches
Height1.0 Inches
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