I learned so many things in this module. I learned that how to do error analysys and different kind of the learning techniques. Thanks Professor Andrew Ng to provide such a valuable and updated stuff.
While the information from this course was awesome I would've liked some hand on projects to get the information running. Nonetheless, the two simulation task were the best (more would've been neat!).
por Alejandro R V•
Not as interesting as the others, I personally prefer math
por Gopala V•
Gave some ideas on mismatched data and how to address them
por Akshita J•
An assignment could have been included to let practically
por Roberto J•
A bit dry, would love to see some more concrete examples.
por Vinicius B F•
Content was fantastic, but the videos were badly edited.
por Suresh P I•
Can be potentially folded into other courses if possible
por Hanqiu D•
It's too easy and cannot be a reasonable single course.
very helpful to build an intuition for DL strategies...
por Rafael G M•
Providing further references would benefit this section
por WEIJIAN K•
You can know well a lot of strategy in machine learning
por B S K•
Good teaching of practical approaches and nice quizzes
the content is good, but the videos are not well made.
por Shuochen Z•
por Gundreddy L M•
excerice should be given for this one proper user case
por Alexey S•
Good class, but 2 previous are much better and useful.
por Lei C•
the answer of the assignment is a little bit arguable.
por SANJAY P•
Content is good. Presentation could have been better.
por Kumari P•
machine learning project are highly iterative as you.
por diego s•
I miss notebooks for practice, besides questionnaires
por Xinghua J•
If there is some coding practice, it would be better
por Pranjal V•
Very well explained but needs more reading material.
por Hee s K•
It is an unique lecture providing empirical advises.
por Pablo L•
Great set of guidelines. Mostly theoretical, though.
por Cristina G F•
Concrete reminders of important and practical points
por Ktawut T•
Very useful materials for leading a ML research team