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Can I read Introduction to Machine Learning (Adaptive Computation and Machine Learning series) on EtoBox?

Introduction to Machine Learning (Adaptive Computation and Machine Learning series) by Ethem Alpaydin is a science book available to read on EtoBox.

What is Introduction to Machine Learning (Adaptive Computation and Machine Learning series) about?

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. The second edition of Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. In order to present a unified treatment of machine learning problems and solutions, it discusses many methods from different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining. All learning algorithms are explained so that the student can easily move from the equations in the book to a computer program. The text covers such topics as supervised learning, Bayesian decision theory, parametric methods, multivariate methods, multilayer perceptrons, local models, hidden Markov models, assessing and comparing classification algorithm

Who reads Introduction to Machine Learning (Adaptive Computation and Machine Learning series)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Ethem Alpaydin
Publisher
MIT Press; Brand: MIT Press; The MIT Press
Published
2010
Language
EN
ISBN
9780262012430
Category
science
Subjects
Engineering, Computer Science, Science
Rating
4.3 / 5 (156 ratings)
Updated
2026-03-14

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