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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

Finances 101

The exercises presented throughout the book are related to historical financial data and require the reader to have some basic understanding of financial markets and reports.

Fundamental analysis

Fundamental analysis is a set of techniques to evaluate a security (stock, bond, currency, or commodity) that entails attempting to measure its intrinsic value by examining related to both macro and micro financial and economy reports. Fundamental analysis is usually applied to estimate the optimal price of a stock using a variety of financial ratios.

Numerous financial metrics are used throughout the book. Here are the definitions of the most commonly used metrics [A:16]:

Earnings per share (EPS): This is the ratio of net earnings over number of outstanding shares.
Price/Earnings Ratio (PE): This is the ratio of market price per share over earnings per share.
Price/Sales Ratio (PS): This is the ratio of market price per share over gross sales (or revenue).
Price/Book Value Ratio (PB): This...

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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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