You can run and experiment with the code using free online resources, try executing this notebook by click the "launch" button above.
Or by going to this link
For using Streamlit UI, install Docker on local machine & clone the repo then use docker build & run commands to see it action!
- Explored 72k plus rows of data.
- Scaled, imputed and encoded the data using scikit-learn.
- Trained and experimented with Logistic Regression, Decision Tree and Random Forest classification models.
- Achieved 90% test accuracy after tuning hyperparameters using Random Forest model.