Machine Learning Foundations - Supervised, Unsupervised, and Advanced Learning (Hardcover, 1st ed. 2021)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Release date:	February 2021
First published:	2021
Authors:	Taeho Jo
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	391
Edition:	1st ed. 2021
ISBN-13:	978-3-03-065899-1
Categories:	Books > Business & Economics > Business & management > Business mathematics & systems > General Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning Promotions
LSN:	3-03-065899-6
Barcode:	9783030658991

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