Suggestions for Part 2 Machine Learning

After watching all the Deep Learning courses, I went back and found this foundation very good with great coverage of Random Forests and Decision Trees.

Now, I’m on Kaggle and everyone is using stuff like LightGBM and Blending, and Ensembles and often winning with them it seems.

So I would love to see an updated version,or Part 2 of this course including the following topics:

LightGBM (seems to be a whole world)
Blending and Ensembles
Advanced Cross-Validation techniques
Grid Search and advanced Hyperparameter tuning methods

Thanks !


I would happily contribute in whatever way possible to a “Part 2 ML” or whatever the update to this course might be in the future. :slight_smile: