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Ratings and Reviews for Applied Machine Learning in Python

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Reviews and Ratings

4.6

7655 Ratings from Coursera

Reviews

Great Course. I love the way it is designed, delivered. I learned a lot. The most important part is that I enjoy every bit of the session and completed everything less than a week,
Awesome for intermediate learners
Great! Fun and useful course. Concepts explained well.
Excellent course material and challenging evaluation components !!
Very well presented. The content is on the correct depth, and very much practical.
This is an excellent course. If you will complete all exercises making sure you complete all questions in each exercise and score almost 100% in each quiz then you will get full value out of course. Deadlines can be reset any time so you can resume courses anytime and you can take your own time as per your schedule. The programming exercises can be solved only when you get the basics right. Else, you will need to revisit the course material.
This course is all over the place, and compared to the previous courses in this specialization, this seems like more of an effort to gloss over the documentation and capabilities of SciKit Learn rather than focusing on a handful of the most important ones. The course lacks focus, the material taught is not rich, and you are better off just reading the documentation on your own. The book recommended at the start of the course is excellent, and reading that instead might be more fruitful for you.
Overall a good course! It was really what I was looking for: main focus is on how to apply algorithms and pros and cons of each model, instead of exhaustively explaining the theory behind each one, like some others courses do. The downside was the grade system. The platform has a lot of potential, but crashes all the time and there are many errors to troubleshoot when submitting assignments. The time invested to troubleshoot these problems was really frustrating, and probably the main reason i won't continue with the specialization.
Week 2 assignment is hard to solve. My appeal is to review the questions again and make it easy.
Good course, but take it with a theoretical course also, (I suggest Learning from Data, Caltech, the lectures are on youtube and assignments are put up online). This one goes well with it, because LFD teaches to code up classifiers and regressors without libraries and this one teaches us practical use of scikitlearn.

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