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Implementations and Applications of Machine Learning

This book provides step-by-step explanations of successful implementations and practical applications of machine learning. The book’s GitHub page contains software codes to assist readers in adapting materials and methods for their own use. A wide variety of applications are discussed, including wir...

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Bibliographic Details
Other Authors: Subair, Saad (Editor), Thron, Christopher (Editor)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2020, 2020
Edition:1st ed. 2020
Series:Studies in Computational Intelligence
Subjects:
Health Informatics
Bioinformatics
Computational Intelligence
Applied Dynamical Systems
Medical Informatics
Data Mining
Nonlinear Theories
Telecommunication
Communications Engineering, Networks
Data Mining And Knowledge Discovery
Dynamics
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • Introduction
  • Part 1: Machine learning concepts, methods, and software tools
  • Overview
  • Classifying algorithms
  • Support vector machines
  • Bayes classifiers
  • Decision trees
  • Clustering algorithms
  • k-means and variants
  • Gaussian mixture
  • Association rules
  • Optimization algorithms
  • Genetic algorithms
  • Swarm intelligence
  • Deep learning,- Convolutional neural networks (CNN)
  • Other deep learning schema
  • Part 2: Applications with implementations
  • Protein secondary structure prediction
  • Mapping heart disease risk
  • Surgical performance monitoring
  • Power grid control
  • Conclusion

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