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Scala Machine Learning Projects

You're reading from Scala Machine Learning Projects

Product type Book

Published in Jan 2018

Publisher Packt

ISBN-13 9781788479042

Pages 470 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Table of Contents (17) Chapters

Title Page

Packt Upsell

Contributors

Preface

1. Analyzing Insurance Severity Claims

2. Analyzing and Predicting Telecommunication Churn

3. High Frequency Bitcoin Price Prediction from Historical and Live Data

4. Population-Scale Clustering and Ethnicity Prediction

5. Topic Modeling - A Better Insight into Large-Scale Texts

6. Developing Model-based Movie Recommendation Engines

7. Options Trading Using Q-learning and Scala Play Framework

8. Clients Subscription Assessment for Bank Telemarketing using Deep Neural Networks

9. Fraud Analytics Using Autoencoders and Anomaly Detection

10. Human Activity Recognition using Recurrent Neural Networks

11. Image Classification using Convolutional Neural Networks

1. Other Books You May Enjoy

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Index

Scala Play web service

As an application framework, Play2 was chosen as an easy-to-configure and robust framework. Compared to Spring (another popular framework), it takes less time to make a small app from scratch. The Play comes with Guice for dependency injection and SBT as the package manager:

Spark ML: The Spark ML library was chosen as it is one of the best-maintained libraries in the Java world. Many algorithms not available in the library itself are implemented by third-party developers and can be trained on top of Spark. A drawback of Spark is that it is quite slow, as by design it is supposed to be distributed; so it uses Hadoop and writes a lot into the filesystem.
Akka: This allows implementing the actor's pattern—having several instances of independent objects and passing messages to each other concurrently, which increases robustness.
Anorm: The library to work with SQL on top of JDBC. Slick is another option and it is more powerful, but compatibility issues between libraries...

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