Machine Learning DevOps - ML Pipeline - Telco Customer Churn Prediction

This repo if for Machine Learning DevOps project based on Telco Customer Churn Prediction

This pipeline consists of following stages:

1. Getting data from the data source
2. Data Cleaning
3. Train, val, test set data split
4. Model training

Current Stage: Built Reproducible Model Workflow

Weights and Biases project screenshot:

Metrics:

Trained on Random Forest Model available on scikit-learn package. Achieved accuracy random forest model is 79% and this is not what maximum can be done with this dataset and random forest model.

TODO list:

1. Build Reproducible Model Workflow DONE ✅
2. Deploy a Scalable ML Pipeline in Production
3. ML Model Scoring and Monitoring