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Mastering Java Machine Learning

You're reading from   Mastering Java Machine Learning A Java developer's guide to implementing machine learning and big data architectures

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Product type Paperback
Published in Jul 2017
Publisher Packt
ISBN-13 9781785880513
Length 556 pages
Edition 1st Edition
Languages
Concepts
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Authors (2):
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 Kamath Kamath
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Kamath
Krishna Choppella Krishna Choppella
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Krishna Choppella
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Table of Contents (20) Chapters Close

Mastering Java Machine Learning
Credits
Foreword
About the Authors
About the Reviewers
www.PacktPub.com
Customer Feedback
Preface
1. Machine Learning Review 2. Practical Approach to Real-World Supervised Learning FREE CHAPTER 3. Unsupervised Machine Learning Techniques 4. Semi-Supervised and Active Learning 5. Real-Time Stream Machine Learning 6. Probabilistic Graph Modeling 7. Deep Learning 8. Text Mining and Natural Language Processing 9. Big Data Machine Learning – The Final Frontier Linear Algebra Probability Index

References


  1. G. Cormode and S. Muthukrishnan (2010). An improved data stream summary: The Count-Min sketch and its applications. Journal of Algorithms, 55(1):58–75, 2005.

  2. João Gama (2010). Knowledge Discovery from Data Streams, Chapman and Hall / CRC Data Mining and Knowledge Discovery Series, CRC Press 2010, ISBN 978-1-4398-2611-9, pp. I-XIX, 1-237.

  3. B. Babcock, M. Datar, R. Motwani (2002). Sampling from a moving window over streaming data, in Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms, pp.633–634, 2002.

  4. Bifet, A. and Gavalda, R. (2007). Learning from time-changing data with adaptive windowing. In Proceedings of SIAM int. conf. on Data Mining. SDM. 443–448.

  5. Vitter, J. (1985). Random sampling with a reservoir. ACM Trans. Math. Softw. 11, 1, 37–57.

  6. Gama, J., Medas, P., Castillo, G., and Rodrigues, P. (2004). Learning with drift detection. In Proceedings of the 17th Brazilian symp. on Artif. Intell. SBIA. 286–295.

  7. Gama, J., Sebastiao, R., and Rodrigues, P. 2013...

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