Statistical learning using neural networks : a guide for statisticians and data scientists / by Basilio de Braganc̨a Pereira, Calyampudi Radhakrishna Rao, Fábio Borges de Oliveira.
Material type:
TextPublisher: Boca Raton : CRC Press, Taylor & Francis Group, 2020Copyright date: ©2020Edition: First editionDescription: 1 online resource (xiii, 233 pages) : illustrations (black and white)Content type: - text
- computer
- online resource
- 9780429431296
- 0429431295
- 9780429775550
- 0429775555
- 9780429775543
- 0429775547
- 9780429775536
- 0429775539
- Statistics -- Data processing
- Multivariate analysis -- Data processing
- Neural networks (Computer science)
- Computational learning theory
- Statistics -- Methodology
- Python (Computer program language)
- BUSINESS & ECONOMICS / Statistics
- COMPUTERS / Database Management / Data Mining
- COMPUTERS / Machine Theory
- 519.50285/632 23
- QA276.4 .P466 2020eb
Fundamental concepts on neural networks -- Some common neural network models -- Multivariate statistics neural network models -- Regression neural network models -- Survival analysis and other networks.
"This book introduces artificial neural networks to students and professionals. It covers the theory and applications in statistical learning methods with concrete Python code examples. Statistical topics covered include multivariate statistics (Cluster, Classification, Dimension Reduction, Projection Pursuit, Nonlinear Regression) Survival Analysis (Cox Model and Extensions) Control, Chart and Statistical Inference. Illustrative examples will be mainly from medicine, engineering, and economics"-- Provided by publisher.
OCLC-licensed vendor bibliographic record.
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