Deep Learning in Data Analytics - Recent Techniques, Practices and Applications (Paperback, 1st ed. 2022)

This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book's material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Studies in Big Data, 91
Release date:	August 2022
First published:	2022
Editors:	Debi Prasanna Acharjya • Anirban Mitra • Noor Zaman
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	266
Edition:	1st ed. 2022
ISBN-13:	978-3-03-075857-8
Categories:	Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > Knowledge-based systems / expert systems
LSN:	3-03-075857-5
Barcode:	9783030758578

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