Machine Learning Foundations

Supervised, Unsupervised, and Advanced Learning

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Éditeur :

Springer


Paru le : 2021-02-12



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Description

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists of four parts: foundation, supervised learning, unsupervised learning, and advanced learning. The first part provides the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms. The second and the third parts provide understanding of the supervised learning algorithms and the unsupervised learning algorithms as the core parts. The last part provides advanced machine learning algorithms: ensemble learning, semi-supervised learning, temporal learning, and reinforced learning.
Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning;Outlines the computation paradigm for solving classification, regression, and clustering;Features essential techniques for building the a new generation of machine learning.
Pages
391 pages
Collection
n.c
Parution
2021-02-12
Marque
Springer
EAN papier
9783030658991
EAN PDF
9783030659004

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
39
Taille du fichier
11080 Ko
Prix
147,69 €
EAN EPUB
9783030659004

Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
39
Taille du fichier
21934 Ko
Prix
147,69 €

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