Ratings and Reviews for Applied Machine Learning in Python

Not very good compared to the first two courses :( :( :( ... I took a Machine Learning Class from Stanford which was incredibly well put together and presented (though to be fair, it was 12 weeks), but it was in MatLab and I wanted to take a course in Python just to have a different perspective and solidify my understanding. Unfortunately, I find this course to be confusing more than anything. If I hadn't taken the Stanford course before, I'd be completely lost. It's very dry, dense, and hand-wavy and doesn't go into a whole lot of details with anything leaving you wondering what's happening and why and how... I don't approve of jumping straight to using the built-in functions if you don't understand the processes behind them (which I personally don't have a solid grasp on them still) ... I think they are just trying to fit too much information into four weeks and it's really lacking. Maybe if you're already familiar with linear regression, it's not as hard to follow. Either way, I'd recommend either taking the Stanford class first, or learning about this stuff elsewhere before starting this course.

I completed the Machine Learning Specialization Certificate before taking this course. This course is an excellent applied course that quickly gets into the key aspects of using sklearn. This course is ideal for both new learners and experienced learners who just want to learn more/revise about machine learning. For the final assignment, it requires substantial data cleaning techniques covered in Course 1 in this specialisation. Overall, I feel very comfortable with using Python for any reasonable size of machine learning problems after taking this course.

Very well designed courses! There are many materials to go in depth even if you have done Python Machine Learning in the past.

Great content and good assignments! Learned a lot from it.

The course is well balanced but the progression becomes quite agressive at Week3 and culminate at Week4 with a real life case assignment without much guidance. Great experience dough.

Excellent material and tutoring!

Very helpful and well-structured course, clear lecturing, and high-level assignments. I hope, however, if it can be offered another course specialized in unsupervised learning in ML.

Great course! Really appreciated it, it taught me (and gave me lots of practice) how to use lots of different classifiers for machine learning.

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