week 2 and week3 are disorganized - the examples don't run without making modifications based on information in the forums.

However the overall course is worth it. I hope they pay more attention to making the examples accessible and making them work.

One example in case of text classification could have been theoretically worked out. For example classification using RNN/LSTM. How a word vector is passed as input to one unit of lstm? To view in on paper would make concepts more clear.

The course is good but lacks graded coding homeworks, these are the most powerful learning tools and it involves reflecting upon the matter, even if they have bugs or version mismatches, they are the most important learing tool!

Good overview but the assignments seem a bit disconnected from the classes at times (e.g. when asking us to use regularizers). Transformers are a lot more popular now and they were not touched on in the course.

The exercises were unclear and ungraded. It is essential to apply the skills learnt from videos. The programming assignment should be made graded and its comments should be descriptive as well.

Not as good as the previous courses of the specialization. It is not as engaging, maybe it is the lack of rated exercises, but maybe also the contents are not taught as well as previously.

Too basic for me. I was hoping for some nice hands-on Tensorflow (not Keras) tutorials. Some deeper modeling and understanding. Good for children :), although they now know more than me.

I got the basic idea behind the sequence models while lots of code shown in the course are used to deal with the text and prepare for the training, which leaves a huge knowledge gap.

I guess there should have been a bit more explanation of the techniques used to provide a bit more understanding rather than just skimming from 50000 ft instaed of atleast 20000 ft.

The Course gives some nice code snippets one can reuse, but it just forms a starting point. In General the Course does go into any depth and I would recommend it only to beginners.

There were some prerequisites of the course related to deeplearning, which should have been known, then the course would have been understood better.

This course was really useful. You always work from a practical point of view, although there are not enough exercises to acquire a remarkable ease.

I was expecting a complete course to master tensorflow but Laurence barely taught tensorflow in this specialization. It was more of introduction.

There weren't any graded Exercise like other courses, which would've made us think a lot more.

I hope they add graded exercise to this course.

It's shallow, does not explain some important concepts. Seems like it was explained on a rush, or didn't bother going more into detaisl.

I would like to implement programming exersice with rate because you can discuss with all the community and you enrich your knowledge.

Good starter course for NLP with Keras. But, I'd say doing Sequence Models ie C5 of the Deep Learning specialization is a must!

Please make the "Ungraded assignment" Graded and add more comments/directive in them to make sure we understand each steps.

It's ok and certainly takes less time than expected, but it's a shame that there are not coding graded exercises.

I feel that the course content is lacking in depth. Usually a week of materials can be finished in a few hours.

Detailed Description is still missing, makes you sometime to google and find the exact understanding.

Homework was almost not existent. Notebooks provided had several mistakes in them. I expected more.

The course is overall good . If you are proficient in python then it would be very easy for you.

Concepts are explained less as compared to a great course on convolutional network course-2

I wish there are more hands-on practice projects and more explanations of the NLP concepts.