Deep Learning in Data Analytics (Hardcover)

Debi Prasanna Acharjya

ISBN 10: 3030758540 / ISBN 13: 9783030758547

Published by Springer Nature Switzerland AG, Cham, 2021

About this Item

Hardcover. 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. This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9783030758547

Bibliographic Details

• Title: Deep Learning in Data Analytics (Hardcover)
• Publisher: Springer Nature Switzerland AG, Cham
• Publication Date: 2021
• Language: English
• ISBN 10: 3030758540
• ISBN 13: 9783030758547
• Binding: Hardcover
• Condition: new

About this title

Synopsis

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.

About the Author