Thank you! and what next?

[jtobelem]

Thank you so much for the instructors!! It was so intersting to practice on the stuff you prepared! It was a great opportunity to discover such state of the art of using sklearn.

As a trainer, I really appreciated the quality of the pedagocial approach and really like the balance between explnation (notebook oriented) and practice.

Would you recommand some project to practice on, or some field to continue on Machine Learning?

[lesteve]

Thanks for the kind words, this is very much appreciated!

A general comment is that trying to use what you have learned on your data or data that you care about is a great way to practice. Also some people like data challenges for example Kaggle and others.

There were also suggestions about what to do next (books or resources) in these topics

Bibliography

Nice introduction. I would appreciate if you recommend boobks to follow the subject in depth

Post Course Completion Suggestion

There is also some more advanced tutorial and example in the scikit-learn documentation: Examples — scikit-learn 0.24.2 documentation