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Supervised and Unsupervised Learning for Data Science /

This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are included along with theoretical models of learning for a compre...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Berry, Michael W. (Editor), Mohamed, Azlinah (Editor), Yap, Bee Wah (Editor)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2020.
Edition:1st ed. 2020.
Series:Unsupervised and Semi-Supervised Learning,
Subjects:
Electrical engineering.
Signal processing.
Image processing.
Speech processing systems.
Pattern recognition.
Artificial intelligence.
Data mining.
Communications Engineering, Networks.
Signal, Image and Speech Processing.
Pattern Recognition.
Artificial Intelligence.
Data Mining and Knowledge Discovery.
Electronic books.
Online Access:Connect to the full text of this electronic book

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