Bewertung und Feedback des Lernenden für Machine Learning Foundations: A Case Study Approach von University of Washington

great course. This covers all types of machine learning techniques deep enough to get a basic idea how things work. Enjoyed a lot. Instructors are really fun to learn from.

Loving it so far! Can't wait for the other courses. The case study approach is spot on! This is the first coursera course that is worth something! Kudos to the instructors.

Nice overview to ease into all the content!, Only bad this is they use sframe :( either make it opensource and in the mainstream use or provide the assignments in sklearn!

A very informative beginners cource which offers a macro view of different approaches to MachineLearning and prepaes the student for further study in each different areas.

Great for a start.

Still has some issues for those who use sklearn and pandas.

Also I'd prefer to see more detailed info on neural networks instead of deep learning module.

E​xcellent course that spans the broad ML domain. Unfortunately it appears that the specialization ends sooner than what was planned, but remains quite good nevertheless.

They have used graphlab instead of using standard library. But overall good course.

If the student can submit quiz question without enrolling then it would be a big plus.

The instructors were fantastic, the material was understandable, and the reach I have beyond this course is still expanding. Thank you for a wonderful learning experience

I found this course as a great introduction to the world of machine learning with a very practical approach.

I'm waiting forward to the next courses in the specialization.

I loved this course! It is really well done, that you have a theory part and a practical "case study" part, were you can follow along with the provided IPython Notebooks.

An excellent course to get introduced to the field of Machine Learning. Amazing professors! And actually putting the knowledge into practice with Python was a big bonus.

This course is designed in a very planned way. It gives you a bird's eye view of the ML world without boggling down you with too much technicalities. Highly recommended.

A good theory and practical based overview of major machine learning tasks. Hands-on practice using GraphLab Create makes it one of the best courses in Machine Learning.

An immaculate course to get your basics and facts right to get a head start in ML.The mentors did their part well. I strongly recommend the vert course to the aspirants

Very good theory and practical approach. However, some of the assignments are not very clear while explaining the questions due to which sometimes we get wrong results.

The instructors are very professional, straight-to-the-point, and they have a nice sense of humor :)

which made the course much more interesting. Definitely recommended!

I really like this course. I've learned basics of ML. I've really enjoyed the presentation style. The practical part was great. I am looking forward to the next course.

Clear and fun instruction. The course gave relevant and tangible examples of machine learning in practice and the coding was very managable for a non-systems engineer.

Great introduction to Machine Learning and the different ML methods. Assignments were not mean to be hard, but practical, which I appreciate. Great instructors as well!

This is a fantastic course. The concepts are explained so well and are followed by hands-on which helps a lot. Case Study approach really is working well in this case.

Great presentation of the topic and fitting complexity / depth for an introduction.

Way better then all the other courses i tried before. Great instructors and concept!

This is a nice introduction to the concepts that will be covered in the specialization and the power of the provided GraphLab Create ML toolbox. I highly recommend it.

This is a really good intro course. It's not pitched at a terribly high level of difficult, but it does give you a fair amount of practice. I'm really pleased with it.

Very informative in basics of Machine Learning. It sets the stage for a deep dive into the topics of machine learning like Regression, Classification, Clustering etc.

This course is really useful, as a overview of the whole specialization. The quiz for theory and python implementation strengthen the key points for each module/week.