Implementations and applications of machine learning

著者

    • Subair, Saad
    • Thron, Christopher

書誌事項

Implementations and applications of machine learning

Saad Subair, Christopher Thron editors

(Studies in computational intelligence, v. 782)

Springer, c2020

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注記

Includes bibliographical references and index

内容説明・目次

内容説明

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 wireless mesh network and power systems optimization; computer vision; image and facial recognition; protein prediction; data mining; and data discovery. Numerous state-of-the-art machine learning techniques are employed (with detailed explanations), including biologically-inspired optimization (genetic and other evolutionary algorithms, swarm intelligence); Viola Jones face detection; Gaussian mixture modeling; support vector machines; deep convolutional neural networks with performance enhancement techniques (including network design, learning rate optimization, data augmentation, transfer learning); spiking neural networks and timing dependent plasticity; frequent itemset mining; binary classification; and dynamic programming. This book provides valuable information on effective, cutting-edge techniques, and approaches for students, researchers, practitioners, and teachers in the field of machine learning.

目次

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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詳細情報

  • NII書誌ID(NCID)
    BB31668109
  • ISBN
    • 9783030378295
  • 出版国コード
    sz
  • タイトル言語コード
    eng
  • 本文言語コード
    eng
  • 出版地
    Cham
  • ページ数/冊数
    xii, 280 p.
  • 大きさ
    25 cm
  • 親書誌ID
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