EAN: 9780262044691

FUNDAMENTALS OF MACHINE LEARNING FOR PREDICTIVE...

The second edition of a comprehensive introduction to machine learning approaches used in
predictive data analytics  covering both theory and practice. Machine learning is often used to
build predictive models by extracting patterns from large datasets. These models are used in
predictive data analytics applications including price prediction  risk assessment  predicting
customer behavior  and document classification. This introductory textbook offers a detailed
and focused treatment of the most important machine learning approaches used in predictive data
analytics  covering both theoretical concepts and practical applications. Technical and
mathematical material is augmented with explanatory worked examples  and case studies
illustrate the application of these models in the broader business context. This second edition
covers recent developments in machine learning  especially in a new chapter on deep learning 
and two new chapters that go beyond predictive analytics to cover unsupervised learning and
reinforcement learning.The book is accessible  offering nontechnical explanations of the ideas
underpinning each approach before introducing mathematical models and algorithms. It is focused
and deep  providing students with detailed knowledge on core concepts  giving them a solid
basis for exploring the field on their own. Both early chapters and later case studies
illustrate how the process of learning predictive models fits into the broader business
context. The two case studies describe specific data analytics projects through each phase of
development  from formulating the business problem to implementation of the analytics solution.
The book can be used as a textbook at the introductory level or as a reference for
professionals.

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