Book Image

Machine Learning with Scala Quick Start Guide

By : Md. Rezaul Karim, Ajay Kumar N
Book Image

Machine Learning with Scala Quick Start Guide

By: Md. Rezaul Karim, Ajay Kumar N

Overview of this book

Scala is a highly scalable integration of object-oriented nature and functional programming concepts that make it easy to build scalable and complex big data applications. This book is a handy guide for machine learning developers and data scientists who want to develop and train effective machine learning models in Scala. The book starts with an introduction to machine learning, while covering deep learning and machine learning basics. It then explains how to use Scala-based ML libraries to solve classification and regression problems using linear regression, generalized linear regression, logistic regression, support vector machine, and Naïve Bayes algorithms. It also covers tree-based ensemble techniques for solving both classification and regression problems. Moving ahead, it covers unsupervised learning techniques, such as dimensionality reduction, clustering, and recommender systems. Finally, it provides a brief overview of deep learning using a real-life example in Scala.
Table of Contents (9 chapters)

Developing predictive models for churn

Accurate identification of churn possibility can minimize customer defection if you first identify which customers are likely to cancel a subscription to an existing service, and offering a special offer or plan to those customers. When it comes to employee churn prediction and developing a predictive model, where the process is heavily data-driven, machine learning can be used to understand a customer's behavior. This is done by analyzing the following:

  • Demographic data, such as age, marital status, and job status
  • Sentiment analysis based on their social media data
  • Behavior analysis using their browsing clickstream logs
  • Calling-circle data and support call center statistics

An automated churn analytics pipeline can be developed by following three steps:

  1. First, identify typical tasks to analyze the churn, which will depend on company...