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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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Table of Contents (15) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Hello World! 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

Finances 101

The exercises presented throughout this 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 examination 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 this book. Here are the definitions of the most commonly used metrics [A:16]:

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