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Scala for Machine Learning, Second Edition

You're reading from   Scala for Machine Learning, Second Edition Build systems for data processing, machine learning, and deep learning

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Product type Paperback
Published in Sep 2017
Publisher Packt
ISBN-13 9781787122383
Length 740 pages
Edition 2nd Edition
Languages
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Author (1):
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Patrick R. Nicolas Patrick R. Nicolas
Author Profile Icon Patrick R. Nicolas
Patrick R. Nicolas
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Table of Contents (21) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Data Pipelines 3. Data Preprocessing 4. Unsupervised Learning 5. Dimension Reduction 6. Naïve Bayes Classifiers 7. Sequential Data Models 8. Monte Carlo Inference 9. Regression and Regularization 10. Multilayer Perceptron 11. Deep Learning 12. Kernel Models and SVM 13. Evolutionary Computing 14. Multiarmed Bandits 15. Reinforcement Learning 16. Parallelism in Scala and Akka 17. Apache Spark MLlib A. Basic Concepts B. References Index

Chapter 2

[2:1] Scientific modeling Wikipedia the Free encyclopedia, Wikimedia Foundation http://en.wikipedia.org/wiki/Scientific_modelling

[2:2] Inside F# Brian's thoughts on F# and .NET: Pipelining in F# - 2008 http://lorgonblog.wordpress.com/2008/03/30/pipelining-in-f/

[2:3] Programming in Scala 2nd edition §17 Collections, M. Odersky, L. Spoon, B. Venners - Artima 2008

[2:4] Programming in Scala 2nd edition §12.5 Traits as stackable modification, M. Odersky, L. Spoon, B. Venners - Artima 2008

[2:5] Dependency Injection in Scala: Cake Pattern V. Mencik, J, Janecek, M. Prihoda - Czech Scala Enthusiasts 2013: http://www.slideshare.net/czechscala/dependency-injection-in-scala-part

[2:6] Dependency Injection in Scala: Extending the Cake pattern A. Warski Blog of Adam Warski 2010: http://www.warski.org/blog/2010/12/di-in-scala-cake-pattern

[2:7] Introduction to Machine Learning §14.2 Cross-Validation and Resampling Methods E. Alpaydin – MIT Press 2004-2007

[2:8]...

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