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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

Naïve Bayes and text mining

The extraction of the most relevant features to build a model relies on discovery and data mining. For many applications, the data available to the scientist is unstructured text. The multinomial Naïve Bayes classifier is particularly suited for text mining.

The Naïve Bayes formula is quite effective to classify the following entities:

E-mail spams
Business news stories
Movie reviews
Technical papers per field of expertise

This third use case consists of predicting the direction of a stock given the financial news. There are two types of news that affects the stock of a particular company:

Macro trends: This consists of the economic or social news such as conflicts, economic trends, or labor market statistics
Micro updates: This consists of the financial or market news related to this specific company such as earnings, change in ownership, or press releases

Micro-economic news related to a specific company has the potential to affect the sentiment of investors toward...

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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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