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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

Mathematical notations for the curious

Each chapter contains a small section dedicated to the formulation of the algorithms for those interested in the mathematical concepts behind the science and art of machine learning. These sections are optional and defined within a tip box.

For example, the mathematical expression of the mean and the variance of a variable, X, as mentioned in a tip box will be as follows:

Note

Convention and notation

This book uses the 0 zero-based indexing of datasets in mathematical formulas.

M1: A set of N observations is denoted as {x_i} = x₀, x₁ …., x_N-1 and the arithmetic mean value for the random value with xi as values is defined as:

Mathematical notations for the curious

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Scala for Machine Learning, Second Edition - Second Edition

Published in: Sep 2017

Publisher: Packt

ISBN-13: 9781787122383

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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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