Back to Machine Learning with PySpark: Customer Churn Analysis
Learner Reviews & Feedback for Machine Learning with PySpark: Customer Churn Analysis by Coursera Project Network
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About the Course
This 90-minute guided-project, "Pyspark for Data Science: Customer Churn Prediction," is a comprehensive guided-project that teaches you how to use PySpark to build a machine learning model for predicting customer churn in a Telecommunications company. This guided-project covers a range of essential tasks, including data loading, exploratory data analysis, data preprocessing, feature preparation, model training, evaluation, and deployment, all using Pyspark. We are going to use our machine learning model to identify the factors that contribute to customer churn, providing actionable insights to the company to reduce churn and increase customer retention. Throughout the guided-project, you'll gain hands-on experience with different steps required to create a machine learning model in Pyspark, giving you the tools to deliver an AI-driven solution for customer churn. Prerequisites for this guided-project include basic knowledge of Machine Learning and Decision Trees, as well as familiarity with Python programming concepts such as loops, if statements, and lists.
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1 - 3 of 3 Reviews for Machine Learning with PySpark: Customer Churn Analysis
By Judy S
•Jun 29, 2023
Explanation is very clear and easy to understand. Well structure.Many thanks.
By Aman P
•Dec 2, 2024
Helpful in clearing concepts
By Nitin B
•Mar 15, 2024
very simple and easy to understand approach