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Scala Machine Learning Projects

You're reading from   Scala Machine Learning Projects Build real-world machine learning and deep learning projects with Scala

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Product type Paperback
Published in Jan 2018
Publisher Packt
ISBN-13 9781788479042
Length 470 pages
Edition 1st Edition
Languages
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Author (1):
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Md. Rezaul Karim Md. Rezaul Karim
Author Profile Icon Md. Rezaul Karim
Md. Rezaul Karim
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Table of Contents (13) Chapters Close

Preface 1. Analyzing Insurance Severity Claims FREE CHAPTER 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 12. Other Books You May Enjoy

Why do we perform churn analysis, and how do we do it?

Customer churn is the loss of clients or customers (also known as customer attrition, customer turnover, or customer defection). This concept was initially used within the telecommunications industry when many subscribers switched to other service providers. However, it has become a very important issue in other areas of business, such as banks, internet service providers, insurance companies, and so on. Well, two of the primary reasons for churn are customer dissatisfaction and cheaper and/or better offers from the competition.

As you can see in Figure 1, there are four possible contracts with the customer in a business industry: contractual, non-contractual, voluntary, and involuntary. The full cost of customer churn includes both the lost revenue and the (tele-) marketing costs involved with replacing those customers...

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