Here I used streamlit to visualize a dataset, perform some quary on it, and finally train a machine learning model using sklearn. Finally I plotted some basic curve like ROC-AUC, Precision-Recall and confusion matrix on fly.
All instruction are provided here

• Dataset can also be founf from here

• change the line no 20 in app.py to provide the data path
• open cmd
• cd over the ML_visualizer
• to install depencies pip install -r requirements.txt
• run the command streamlit run app.py
• hopefully it is running on http://localhost:8501

1. install git on your system, if not already present. Then run these 3 command in cmd
   git init
   git add .
   git commit -m "Initial commit"
2. install heroku exe and run these line in cmd
   heroku login
   heroku create
   git push heroku master
   heroku ps:scale web=1
   heroku open

after heroku login command, login in the browser window if it opens. Hopefully, after completing the above steps your app is successfully deployed and running.
NOTE : if you are deploying your web app on the cloud (not local machine), you may encounter wrong values of time shown in the raw data in date-time column (more details here)