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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

What you need for this book

A decent command of the Scala programming language is a prerequisite. Reading through a mathematical formulation, conveniently defied in an information box, is optional. However, some basic knowledge of mathematics and statistics might be helpful to understand the inner workings of some algorithms.

The book uses the following libraries:

Scala 2.11.8 or higher
Java 1.8.0_25
SBT 0.13 or higher
JFreeChart 1.0.17
Apache Commons Math library 3.5 (Chapter 3, Data Pre-processing, Chapter 4, Unsupervised Learning, and Chapter 9, Regression and Regularization)
Indian Institute of Technology Bombay CRF 0.2 (Chapter 7, Sequential Data Models)
LIBSVM 0.1.6 (Chapter 8, Kernel Models and Support Vector Machines)
Akka 2.3.8 or higher (or Typesafe activator 1.2.10 or higher) (Chapter 16, Parallelism in Scala and Akka)
Apache Spark 2.1.0 or higher (Chapter 17, Apache Spark MLlib)
Tip
Understanding the mathematical formulation of a model is optional.

The rest of the chapter is locked

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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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