Q21

[A M A]

Q21 - Time to say thank-you isn't it ?


Thanks Dr. Yaser and all others. It was a good experience to take this course.


All the best.

Abdulbaset Ali

[ripande]

Yes. Thanks to one and all in this forum who replied to my queries. It made a world of difference.

And special thanks to Prof Yaser, for the fabulous lectures and responding to all the queries from students on this forum so promptly

[yaser]

Q21 .

Thank you all.

[Sendai]

Thanks to you, Professor, and everyone else who helped create this class. I really learned a lot.

[ivankeller]

I want to thank a lot Pr. Abu-Mostafa and all the people who participate to make this excellent course possible.
I've learned so much in a different focus than another ML course I've taken before from Pr. Andrew Ng (Stanford UNiversity). In comparison, I can say that with your course I understood better the theoretical aspect of statistical learning. Ng's course was a bit more practical.
Ivan Keller.

[heer2351]

Indeed thanks for this course I specifically learned a lot by making the homework.

Some feedback though, I have been doing quite a number of online courses over the last 2 years. What I miss in this course is some elaboration on the answers after the homework is closed.

In other courses the "evaluation" of the answers (also pointing to common mistakes) was very beneficial to the learning experience.

[ilya239]

Originally Posted by ivankeller

Ng's course was a bit more practical.

Actually I found this course more practical in the sense all solutions were built from scratch (in Ng's course you start with template code and fill in the key parts). It's useful to see for yourself that working classifiers can be built from scratch, and to go through some pitfalls of building them.

Thanks a lot Prof. Yaser for all you've put into this course. It's one of the best I've taken. The derivations were precise enough to help with understanding, without unnecessary details. The uniform "learning diagram" will be useful for approaching learning problems systematically. Building small learning systems yourself was good reassurance that this all actually works.

Thanks again, and all the best.

ilya

[robbinsleep]

Looking forward to use what I have learned. Thanks again

Robbin