Ratings and Reviews for Applied Machine Learning in Python

Well-organized but assignments too easy

I'm glad there was an introductory course like this offered for machine learning. The content is very accessible and the assignments are simple enough to work through without frustration, but challenging enough to help you understand how to apply machine learning algorithms on your own. I did purchase the book recommended, Introduction to Machine Learning with Python by Andreas C. Muller and Sarah Guido. The lectures in this course are basically paraphrase the book. Frankly, I think you'd get more value from this course if you read Chapter 2 in its entirety and follow along with the juypter notebooks provide with the book. It's easy to tell when someone is teaching you vs. reading to you— this course's lectures were definitely the latter.

Nice course on machine learning basics!

So far the best course in this specialization

Great course! Superb professor! Very well organized and structured. Lots of useful optional articles and videos. Learned a lot. Thanks!

This could the single most interesting course amongst all the 5 courses in this specialization. It made Machine Learning easy to interpret and fun to explore for beginners. The assignments are very thorough, though with some autograder issues. I strongly recommend anyone who's interested in ML to take this introductory course to again some knowledge in the different methods and applications of ML in various fields.

The course was fantastic.

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The course tries to do too much in four weeks. Consequently, the teaching material isn't as comprehensive as it ought to be. I've probably spent over 10-15 hours cumulatively on other websites, trying to comprehend the intuition behind the algorithms used. This course isn't great at getting that across. There's a lot in here that we're forced to take for granted. I'm afraid I'll have to think twice before I choose other UMich courses in the future.

Everybody has different skill levels, but this was really hard and really, really, really fast. Did I say it was really fast?