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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

Product type Paperback

Published in Sep 2017

Publisher Packt

ISBN-13 9781787122383

Length 740 pages

Edition 2nd Edition

Languages

Scala

Tools

Apache Spark

Concepts

Data Processing

Author (1):

Patrick R. Nicolas

View More author details

Table of Contents (21) Chapters

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

Scala programming

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

List of libraries and tools

The precompile Scala for Machine learning is ScalaMl-2.11-0.99.2.jar located in directory $ROOT/project/target/scala-2.11.

Here is the complete list of recommended tools and libraries used in creating and running the Scala for machine learning:

Java JDK 1.7 or 1.8 for all chapters
Scala 2.11.8 or higher for all chapters
Scala IDE for Eclipse 4.0 or higher
IntelliJ IDEA Scala plug in 13.0 or higher
Sbt 0.13.1 or higher
Apache Commons Math 3.5 or higher for Chapter 3, Data Pre-processing, Chapter 4, Unsupervised Learning, and Chapter 12, Kernel Models and SVM
JFChart 1.0.1 in Chapter 1, Getting Started, Chapter 2, Data Pipelines, Chapter 5, Dimension Reduction, and Chapter 9, Regression and Regularization
Iitb CRF 0.2 (including LBGFS and Colt libraries) in Chapter 7, Sequential Data Models
LIBSVM 0.1.6 in Chapter 8, Monte Carlo Inference
Akka framework 2.3 or higher...

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Authors (1)

R. Nicolas

R. Nicolas

Patrick R. Nicolas is the director of engineering at Agile SDE, California. He has more than 25 years of experience in software engineering and building applications in C++, Java, and more recently in Scala/Spark, and has held several managerial positions. His interests include real-time analytics, modeling, and the development of nonlinear models.

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