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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

Chapter 2. Analyzing and Predicting Telecommunication Churn

In this chapter, we will develop a machine learning (ML) project to analyze and predict whether a customer is likely to cancel the subscription to his telecommunication contract or not. In addition, we'll do some preliminary analysis of the data and take a closer look at what types of customer features are typically responsible for such a churn.

Widely used classification algorithms, such as decision trees, random forest, logistic regression, and Support Vector Machines (SVMs) will be used for analyzing and making the prediction. By the end, readers will be able to choose the best model to use for a production-ready environment.

In a nutshell, we will learn the following topics throughout this end-to-end project:

Why, and how, do we do churn prediction?
Logistic regression-based churn prediction
SVM-based churn prediction
Decision tree-based churn prediction
Random forest-based churn prediction
Selecting the best model for deployment

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