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Scala for Machine Learning

You're reading from   Scala for Machine Learning Leverage Scala and Machine Learning to construct and study systems that can learn from data

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Product type Paperback
Published in Dec 2014
Publisher
ISBN-13 9781783558742
Length 624 pages
Edition 1st 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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Toc

Table of Contents (15) Chapters Close

Preface 1. Getting Started 2. Hello World! FREE CHAPTER 3. Data Preprocessing 4. Unsupervised Learning 5. Naïve Bayes Classifiers 6. Regression and Regularization 7. Sequential Data Models 8. Kernel Models and Support Vector Machines 9. Artificial Neural Networks 10. Genetic Algorithms 11. Reinforcement Learning 12. Scalable Frameworks A. Basic Concepts Index

Scala programming

The following is a partial list of coding practices and design techniques used throughout the book.

List of libraries

The libraries directory contains the JAR files related to the third-party libraries or frameworks used in this book. Not all libraries are needed for every chapter. The list is as follows:

  • Apache Commons Math 3.3 in Chapter 3, Data Preprocessing; Chapter 4, Unsupervised Learning; and Chapter 6, Regression and Regularization
  • JFChart 1.0.1 in Chapter 1, Getting Started; Chapter 2, Hello World!; Chapter 5, Naïve Bayes Classifiers; and Chapter 9, Artificial Neural Networks
  • Iitb CRF 0.2 (including L-BFGS and Colt libraries) in Chapter 7, Sequential Data Models
  • LIBSVM 0.1.6 in Chapter 8, Kernel Models and Support Vector Machines
  • Akka framework 2.2.4 in Chapter 12, Scalable Frameworks
  • Apache Spark/MLlib 1.1 in Chapter 12, Scalable Frameworks

Tip

Note for Spark developers

The Scala library and compiler JAR files bundled with the assembly JAR file of Apache Spark contain...

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