.

9

The videos are very good. The lab assignments have a problem. For some either the input data is not reachable or the way to retrieve the information via torchtext is obsolete and there is no information related to what version of torchtext to use with what version of pytorch and python as well. It took me days to figure it out, and then how to format the retrieved data so that it can be used for the assignment. I must recognize that it helped me have a better understanding of pytorch but it was very time consuming. If this was the final goal of the assignment, then please update the time to more than an hour of two

I enjoyed Lawrence Carin's explanations a lot but the overall experience was not great I'm afraid. It felt like it did not come together properly. The order of lectures and assignments felt wrong. The Python level of competence was too high for this course and support (via forums) was non-existent. I don't regret finishing the course but I would not recommend it to my friends.

The lectures were great and very easy to follow! However, I found that the assessments were too easy as they comprised solely of multiple choice questions, maybe including hands on coding assessments fo contribute to our final grade would have made me feel more confident that I've grasped what was supposed to be taught to me each week.

Modules need a bit of synchronization.

Please spend some more time explaining gradient descent.

If possible, explain using a board where we could have things simultaneously.

Also, request to have a course on machine vision using CNN etc.

Good introduction to the concepts of machine learning. Somewhat overly repetitive, some inconsistencies. Information is not up to date, for example, the python code for Tensorflow would not work.

The course is generally fine. But the problem is I can't review some of the course material and my assignment, after I've finished the course.

This course is good for just theoretical understanding of the subject. But for practical implementation it is too hard to do.

Thank You team Coursera and Teachers from Duke University for helping me to understan dthe basics of machine learning..

Please increase the audio levels its too low to hear without headphones or external speakers for my laptop

More examples should be provided for each course, and the content needs to be more simplified.

A bit too technical for new learners. More practical exercises will make it more learnable.

The theory is well explained but you guys should update the coding parts to TensorFlow 2.

There are many better ML intro courses out there...poorly structued and delivered.

Only concepts no practice. But the concepts are really well taught according to me

The course requires more detailed intuitive approach towards material preparation

some concepts were difficult to understand and not explained very well

just a basic overview of the methods. not much worth the time

I could not even understand the introduction class

Pretty good introduction to Machine Learning!

Overall good experience

Good well

4.2