Estoy muy emocionada

Update for TF2.0 :)

Looks raw yet.

awful sound

enjoyed :)

Good

good

good

N/A

괜찮음

The videos are good and go into a lot of the details. However, the programming tasks are not very useful. They basically expect you to plug certain lines into an almost complete programme, without really understanding what the individual lines - let alone the rest of the programme - really mean. Also, there is the occasional reference to lecture notes. However, those lecture notes are just the slides that are being used with hand-written annotations on top, and without the accompanying videos, they are not useful.

Good course content and clear exposition by Andrew. The course material however is not of a good standard. The slides can be downloaded but after all the hand scribbles by the tutor, they are barely decifrable. Some are just blank pages that need to be filled in with screenshots from of the videos. The assignements are often just a copy and paste exercise, and Jupyter crashes cause frequent loss of work.

The video content is very good to get a good hang of theoretical aspects but the programming assignments are too spoon-fed because of which after doing filling the blanks, you don't feel confident enough to implement the same on your own. Instead the assignments should be changed to cases where instructions are given in words and entire function should be implemented by students.

The TensorFlow part of the course felt out of place and not of the same quality as the previous material. It would have been better if another week was spent using TensorFlow to actually improving a NN and not just copy-paste an example into the assignment. Even after using TensorFlow in the assigment and passing, working with TensorFlow still

In general the course isn't deep enough. There are no summaries of the lectures, there are no excercises during lectures, the programming assignments are very weak, they don't challenge the use of lectures or anything - all necessary data are in the notebooks. All this course will be lost in a week.

Sadly the last course assignment didn't compile properly in the sections that were outside the "graded functions" (more specifically in Week 3). Also some of the questions of the quizzes were intentionally misleading but for very unimportant details.

They should improve the programming labs.

There's too much repetition in things like programming a function that initializes the parameters while important things, like model definition, are already written in the notebook.

The whole tensor flow introduction is weak - it clearly requires further reading, which is fine but totally out of kilter with the videos so far, which have taken things from first principles very clearly.

A technical problem with the grader caused my grade to be artificially lower on the last project. Although I was instructed to resubmit, the course ended with a lower grade than I should have received.

Not much implementation required of the students. More testing of the methods would be useful or if the concepts are the focus then this course should be merged into another course in the sequence.

The course material is good but Jupyter notebook interface does not work correctly. You will waste a lot of you precious time fiddling and redoing work that you lose when the notebook fails to save.

could be accomplished in a week. wastes time and doesnt go in sufficient depth.

After completion, you will get a 'taste' of optimization techniques, but it is not way comprehensive.

The course was good but there were multiple mistakes in the final programming assignment. These mistakes were reported in the forums over 4 months ago and have not been addressed.

I find that the programming assignments have a LOT of copy pasta. Also, wasn't enthused to hear that we are using an out of data framework.

Very poor explanations, not correlated with the quitz and exercises. Missing more theoretical material in pdf with some more explanations.