Machine learning : theoretical foundations and practical applications / Manjusha Pandey, Siddharth Swarup Rautaray, editors.
Pandey, Manjusha, editor.; Rautaray, Siddharth Swarup, editor.
2021
Q325.5
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Title Machine learning : theoretical foundations and practical applications / Manjusha Pandey, Siddharth Swarup Rautaray, editors.
ISBN 9789813365186 (electronic bk.)
9813365188 (electronic bk.)
9789813365179 (print)
981336517X
DOI https://doi.org/10.1007/978-981-33-6518-6
Published Singapore : Springer, [2021]
Language English
Description 1 online resource (xi, 172 pages) : illustrations (some color).
Item Number 10.1007/978-981-33-6518-6 doi
Call Number Q325.5
Dewey Decimal Classification 006.3/1
Summary 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.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed April 28, 2021).
Added Author Pandey, Manjusha, editor.
Rautaray, Siddharth Swarup, editor.
Series Studies in big data ; v. 87. 2197-6503
Available in Other Form Print version: 9789813365179
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Chapter 1. What do RDMs capture in Brain Responses and Computational Models?
Chapter 2. Challenges and solutions, in developing Convolutional Neural Networks and Long Short Term Memory networks, for industry problems
Chapter 3. Speed, Cloth and Pose Invariant Gait recognition Based Person Identifification
Chapter 4. Applications of Machine learning in industry 4.0
Chapter 5. Web Semantics and Knowledge Graph
Chapter 6. Machine Learning based Wireless Sensor Networks
Chapter 7. AI to Machine Learning:lifeless automation and Issues
Chapter 8. Analysis of FDIs in Different Sectors of the Indian Economy
Chapter 9. Customer Profiling & Retention using Recommendation system and Factor Identification to predict Customer Chur In Telecom Industry.

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