Building an End-to-End ML Solution for Telecom with Databricks

Reducing the Churn Rate of your Customers

Databricks Machine Learning helps ML teams create and process data, streamline cross-team collaboration, enable the ML lifecycle and design ML architectures, and simplify all aspects of data for ML for telecom companies.

In the telecom space, customers tend to select from multiple service providers and regularly switch from one operator to another. Hence, reducing the customer churn rate and predicting when they are at the highest probability of churn is the key.

In this webinar, we will learn how to address the complete end-to-end ML life cycle and discuss a telecom case study through Databricks and its implementation in putting the best ML practices at scale.

Discussion Topics:

What do we mean by end-to-end machine learning?
Challenges involved in creating new ML projects
Principles of managing ML projects
Why use Analytics Dashboard?
Introduction to Databricks
Understand a telecom case study through Databricks [how to reduce customer churn rate]
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