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Hands-On Unsupervised Learning with Python

You're reading from   Hands-On Unsupervised Learning with Python Implement machine learning and deep learning models using Scikit-Learn, TensorFlow, and more

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Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789348279
Length 386 pages
Edition 1st Edition
Languages
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Authors (2):
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Giuseppe Bonaccorso Giuseppe Bonaccorso
Author Profile Icon Giuseppe Bonaccorso
Giuseppe Bonaccorso
Giuseppe Bonaccorso Giuseppe Bonaccorso
Author Profile Icon Giuseppe Bonaccorso
Giuseppe Bonaccorso
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Table of Contents (12) Chapters Close

Preface 1. Getting Started with Unsupervised Learning FREE CHAPTER 2. Clustering Fundamentals 3. Advanced Clustering 4. Hierarchical Clustering in Action 5. Soft Clustering and Gaussian Mixture Models 6. Anomaly Detection 7. Dimensionality Reduction and Component Analysis 8. Unsupervised Neural Network Models 9. Generative Adversarial Networks and SOMs 10. Assessments 11. Other Books You May Enjoy

Further reading

  • Theoretical Neuroscience, Dayan P., Abbott L. F., The MIT Press, 2005
  • Maximum Likelihood from Incomplete Data via the EM Algorithm, Journal of the Royal Statistical Society, Dempster A. P., Laird N. M., and Rubin D. B., Series B. 39 (1), 1977
  • A new look at the statistical model identification, Akaike H., IEEE Transactions on Automatic Control, 19 (6)
  • Variational Learning for Gaussian Mixture Models, Nasios N. and Bors A. G., IEEE Transactions on Systems, Man, and Cybernetics, 36/ 4, 08/2006
  • Belohlavek R., Klir G. J. (edited by), Concepts and Fuzzy Logic, The MIT Press, 2011
  • Chapelle O., Schölkopf B., and Zien A. (edited by), Semi-Supervised Learning, The MIT Press, 2010
  • Mastering Machine Learning Algorithms, Bonaccorso G., Packt Publishing, 2018
  • Machine Learning Algorithms, Second Edition, Bonaccorso G., Packt Publishing, 2018
...
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