Ratings and Reviews for Applied Machine Learning in Python

It's a superb course well organised with good and real time examples.

Great course for learning how to apply Machine Learning algorithms with Python.

This is a very good course about How to apply Machine Learning but I think before taking this course the student should take the Andrew Ng machine learning course by Stanford University to Learn the Important Mathematics behind the ML algorithms But Enjoyed this course a lot thank you

Very nice class for people who have some intermediate knowledge in Python and who want to dig in, or consolidate their knowledge in Machine Learning. Great overview over scikit-learn, also going into details, and I also appreciated the part of the class about model evaluation. First week might seem not overly difficult, but the intensity of the class ramps up significantly in week 2. For me the level was challenging enough, without being overwhelming. I enjoyed taking this class and obtaining my certification at the end was a very nice reward. A big thank you to University of Michigan.

Inspirational course, learning you in a comprehensive manner, a thorough approach to machine learning with the target specific peculiarities and possible pitfalls.

excellent course

A little dated. Overall a good introduction. The informal explanation of SVM was particularly effective.

Optional references to the inner workings should be provided. For example how Decision Trees are trained and how the best division is decided.

A very good course to start journey on data science. Good combination of reading, lecture and practice.

Great course on doing machine learning use sklearn and put little but enough explanation of the theories behind it!