📖
Application of Machine Learning and Data Mining
DOAB Contributor

Application of Machine Learning and Data Mining

Author / Organization:
Open Access Books Published 2024 Verification Pending

Overview & Synopsis

The following special issue contains 14 articles accepted and published in the Special Issue "Mathematics and Computer Science, 2024" of the MDPI journal Mathematics. The included articles cover a wide range of topics related to the theory and applications of Machine Learning and Data Mining, as well as their extensions and generalizations. These topics include, but are not limited to, supervised, unsupervised, and self-learning methods; large-scale data mining; applicable neural networks and artificial intelligence; neural network-based industrial applications; neural models for natural language processing; deep learning for health informatics and biomedical engineering; graph convolutional neural networks and their applications; deep reinforcement learning and its applications; deep sparse and low-rank representation; and computer vision and pattern recognition techniques. In addition to these core areas, the authors of the included articles also delve into advanced methodologies and innovative approaches within these fields. The collection aims to provide comprehensive insights into recent advancements and emerging trends in Machine Learning and Data Mining, making it a valuable resource for researchers, practitioners, and students interested in the latest developments in these dynamic disciplines.

Indexed from repository: Directory of Open Access Books (www.doabooks.org)

Document Information

Document Title Application of Machine Learning and Data Mining
Author / Organization DOAB Contributor
Subject & Discipline epilepsy detection
Categories Open Access Books
Publication Year 2024
License / Rights Open Access / Creative Commons
Resource Verification Listed PDF (Verification Pending)
Original Host Website Directory of Open Access Books (www.doabooks.org)
File Format application/pdf (Portable Document Format)
Language EN
Catalog ID DOC-277876
Original Source Link Visit Source Page on www.doabooks.org »