Machine Learning: Theoretical Foundations and Practical Applications (Hardcover, 1st ed. 2021)

This edited book is a collection of chapters invited and presented by experts at 10th industry symposium held during 9-12 January 2020 in conjunction with 16th edition of ICDCIT. The book covers topics, like machine learning and its applications, statistical learning, neural network learning, knowledge acquisition and learning, knowledge intensive learning, machine learning and information retrieval, machine learning for web navigation and mining, learning through mobile data mining, text and multimedia mining through machine learning, distributed and parallel learning algorithms and applications, feature extraction and classification, theories and models for plausible reasoning, computational learning theory, cognitive modelling and hybrid learning algorithms.

General

Imprint:	Springer Verlag, Singapore
Country of origin:	Singapore
Series:	Studies in Big Data, 87
Release date:	April 2021
First published:	2021
Editors:	Manjusha Pandey • Siddharth Swarup Rautaray
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	172
Edition:	1st ed. 2021
ISBN-13:	978-981-3365-17-9
Categories:	Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	981-3365-17-X
Barcode:	9789813365179

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