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Introduction to Statistical Machine Learning (Paperback)
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Introduction to Statistical Machine Learning (Paperback)
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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 a general 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.
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