All complicated math acknowledges were cut off and fully focused on applying ML using python. As an energy engineering master student who doesn't have much programming experience, I find this course very useful. PS. I've previously taken the specialization 'Python for Everybody' to get familiar with python. I suggest doing the same if you also have no idea of python just like I did when I started.
Ratings and Reviews for Applied Machine Learning in Python
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Reviews and Ratings
Reviews
The course is awesome. Professor Kevyn Collins Thompson, explains the topics with examples in python which makes content easy to understand. It is the best course for beginners.
Good
Lots of material to cover in this course. From supervised learning to the optional un-supervised learning schemes. A good introductory course to all theory there is to know on applied machine learning. The professor gives a glimpse of internal mathematics too. Interesting course, but lot of material to cover.
It was really a good experience. The content is rich and clear and the tools at our disposal are of good quality.
great course, excellent teaching staff
Very enjoyable, informative and I really believe I can go on and build my own ML system with confidence. Recommended.
This is a very good course. Probably, much time should be given, especially for Week 2 and Assignment of Week 4. Thank you very much for the course!
awesome!!!!!!!!
Good Course, i would have liked a little bit more theory about the algorithms, but this is an applied course of ML. Projects are good and the readings are interessting!
