Masterfully done

[AdrienL]

I will add my own words to those already told here : thank you Professor and thanks to all the people who made this possible (the TAs, staff, ...).

The lectures were excellent and delivered with exceptional clarity by the lecturer — I especially enjoyed the well designed slides, the right balance between concepts, their underlying mathematics and illustrative examples. The final Q&As and the exchanges on the discussion forums with the Professor, the TAs and my fellow students helped clear out any interrogations that I had and provided me with more insight on interrogations I did not have .

I don't know if you plan to make other re-runs of this course, but I would definitely advise it to anyone interested in the subject.

Perhaps my only grieves would be, that it took me quite a lot of time to learn new packages towards the end of the course (quadratic programming and libsvm, whose documentations were poor — hopefully the posts on the discussion forums helped me tremendously in dealing with these libraries), and that the interface summarizing the answers on the answer page is not very clear : I usually have to write down my answers on a sheet of paper and the correct answers from the answer key to figure on which I was wrong and on which I was right.

But these are only minor grievances, so, once again, thanks for providing us with this high quality free online course on machine learning.

(I still have to complete the final though ! But after that I will personally try to follow coursera's upcoming probabilistic graphical models course, as well as the course on neural networks and a few others, if my free time allows it )

[janjetin]

I'd like to add my own thanks and commendations to Prof. Yaser Abu-Mostafa and others who are responsible for this course.

The lectures were particularly well conducted and are probably the best lectures I've watched so far, compared to other online courses. Prof. Abu-Mostafa explains the material in clear and very interesting manner, emphasizing the important points that are useful in practical implementations.

Homework and final problem sets were challenging, and enabled me to learn from my mistakes and use the correct answers to correct my hypothesis.

The only thing missing from the course is a large scale programming project dealing with a real learning situation, (i.e. something like the Netflix competition related collaboration the professor talked about in the last lecture).

I'm looking forward to seeing and attending more courses from prof. Abu-Mostafa and Caltech in the future.

[Alejandro Martinez]

Thanks prof. Mostafa!

I really liked the course and the book, both very well done. I think the balance between foundations and practical aspects is really good.

If there are plans for a second part, I would like to participate.

Thanks again, Alejandro.

[ramin]

What a gem this class is! Thanks to the professor for presenting the concepts jargon-free.

[fgpancorbo]

I second the thoughts of the others here. This was a great class and I do believe that prof Abu-Mostafa is one of the best instructors around! My sincere thanks to him and the rest of the staff at Caltech, NTU and RPI for making this experience possible!!!

[kdresser]

+1 to all the above.

I learned more here, both foundational and practical, than in any BSc course I took many decades ago. This course was challenging and rewarding, especially the homeworks. Whew.

I thank Prof. Yaser Abu-Mostafa for creating and teaching this course in his inimitable skill & style, Prof. Malik Mogdan-Ismail and Prof. Hsuan-Tien Lin for their contributions to the discussion threads, all the TA's, and Caltech & its supporters for this valuable course.

Definitely masterfully done.

JKD