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Overview of Multi-Factor Prediction Using Deep Neural Networks, Machine Learning, and Their Open-Source Software

Overview of Multi-Factor Prediction Using Deep Neural Networks, Machine Learning, and Their Open-Source Software

Richard S. Segall
Copyright: © 2022 |Pages: 28
ISBN13: 9781799884552|ISBN10: 1799884554|ISBN13 Softcover: 9781799884569|EISBN13: 9781799884576
DOI: 10.4018/978-1-7998-8455-2.ch001
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MLA

Segall, Richard S. "Overview of Multi-Factor Prediction Using Deep Neural Networks, Machine Learning, and Their Open-Source Software." Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning, edited by Richard S. Segall and Gao Niu, IGI Global, 2022, pp. 1-28. https://doi.org/10.4018/978-1-7998-8455-2.ch001

APA

Segall, R. S. (2022). Overview of Multi-Factor Prediction Using Deep Neural Networks, Machine Learning, and Their Open-Source Software. In R. Segall & G. Niu (Eds.), Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning (pp. 1-28). IGI Global. https://doi.org/10.4018/978-1-7998-8455-2.ch001

Chicago

Segall, Richard S. "Overview of Multi-Factor Prediction Using Deep Neural Networks, Machine Learning, and Their Open-Source Software." In Biomedical and Business Applications Using Artificial Neural Networks and Machine Learning, edited by Richard S. Segall and Gao Niu, 1-28. Hershey, PA: IGI Global, 2022. https://doi.org/10.4018/978-1-7998-8455-2.ch001

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Abstract

This chapter first provides an overview with examples of what neural networks (NN), machine learning (ML), and artificial intelligence (AI) are and their applications in biomedical and business situations. The characteristics of 29 types of neural networks are provided including their distinctive graphical illustrations. A survey of current open-source software (OSS) for neural networks, neural network software available for free trail download for limited time use, and open-source software (OSS) for machine learning (ML) are provided. Characteristics of artificial intelligence (AI) technologies for machine learning available as open source are discussed. Illustrations of applications of neural networks, machine learning, and artificial intelligence are presented as used in the daily operations of a large internationally-based software company for optimal configuration of their Helix Data Capacity system.

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