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Machine Learning and Big Data Analytics (Proceedings of International Conference on Machine Learning and Big Data Analytics (ICMLBDA) 2021): 256 1st ed. 2022 Edition
Author(s): Rajiv Misra (Editor), Rudrapatna K. Shyamasundar (Editor), Amrita Chaturvedi (Editor), Rana Omer (Editor)
- Publisher: Springer
- Publication Date: 30 Sept. 2021
- Edition: 1st ed. 2022
- Language: English
- Print length: 373 pages
- ISBN-10: 3030824683
- ISBN-13: 9783030824686
Book Description
This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets—i.e., big data—to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.
Editorial Reviews
From the Back Cover
This edited volume on machine learning and big data analytics (Proceedings of ICMLBDA 2021) is intended to be used as a reference book for researchers and practitioners in the disciplines of computer science, electronics and telecommunication, information science, and electrical engineering. Machine learning and Big data analytics represent a key ingredients in the industrial applications for new products and services. Big data analytics applies machine learning for predictions by examining large and varied data sets―i.e., big data―to uncover hidden patterns, unknown correlations, market trends, customer preferences, and other useful information that can help organizations make more informed business decisions.
