Machine training: basics, algorithms and practice of application
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Fundamental knowledge and practical tools in the field of machine learning are presented, including more than 100 in -depth exercises in Python. The introduction to machine learning and mathematical optimization is given, including first and second orders, gradient descent and Newton. A complete description of learning with the teacher is given, including linear regression, two -class and multi -class classification, as well as training without a teacher and fundamental methods of generating features. Introduction to nonlinear training with and without a teacher is given. The theme of automated selection of suitable nonlinear models is discussed, including cross validation, busting, regulatory and ensembleing. Counted fixed-circuit nuclei, neural networks, trees and other universal approximators. Separately given a complete interpretation of advanced optimization methods. The electronic archive on the website of the publishing house contains codes of all examples and more than 300 color illustrations
Author:
Author:Katsaggelos aggelos, Borhani Reza, Watt Jeremy
Cover:
Cover:Hard
Category:
- Category:Computer & Technology
Publication language:
Publication Language:Russian
ISBN:
ISBN:978-5-975-6763-3
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