You’ve built your Machine Learning model with 99% accuracy and now you are ecstatic. You are like yaaaaaaaaay! My model performed well.
Then you paused and you were like – now what?
Well first, you might have thought of uploading your code to GitHub and showing people your Jupyter notebook file. It comprises those gorgeous-looking visualizations you created using Seaborn, those extremely powerful ensemble models, and how they are able to pass their evaluation metrics and so on.