Machine Learning Project in R- Predict the customer churn of telecom sector and find out the key drivers that lead to churn. Learn how the logistic regression model using R can be used to identify the customer churn in telecom dataset.
Estimating churners before they discontinue using a product or service is extremely important. In this ML project, you will develop a churn prediction model in telecom to predict customers who are most likely subject to churn.
This is a typical Big Data ETL visualization project implemented in AWS cloud using cloud native tools like Glue which is used to Spark jobs without maintaining cluster infrastructure, Step Functions which is used to schedule jobs based on dependency ,Redshift which is the ultimate petabyte scale data warehouse solution in AWS and Quicksight which is AWS managed Visualization tool to create business reports
In this machine learning project, you will uncover the predictive value in an uncertain world by using various artificial intelligence, machine learning, advanced regression and feature transformation techniques.