Full of appalling errors that have been present for over 1 year. No one fixes it. It is clear that since Ng was let go by Stanford and Baidu, he is trying to earn a living with deep learning_ai. This apparently is not working as the small income from Coursera is not sufficient. As a result the prerecorded classes remain on Coursera to accrue some residual income. But, Andrew Ng and the staff are apparently gone.

Sadly, since these classes are no longer based on REAL Stanford classes the quality has gone downhill. I would recommend not taking the deeplearng_ai classes. Stick to classes offered by currently employed professors at established universities--preferably classes that ARE the same as the university classes or, at least, those derived from actual classes.

I really like the deeplearning.ai specialization. And also I like the Sequence Models course. However, I feel that I have learned less during this course comparing to the other ones in the specialization. First, I believe it was an extensive use of Keras. Whereas the framework is great, it would be much better for understanding if all the exercises were in numpy, whereas Keras tween-projects be optional. Doing both numpy and Keras versions would allow to better understand the material and learn through repetition. Second, even though the course is great, I perceived the number of errors/typos was much higher than in other courses. Is that true? For example, the Jazz Improvisation exercise was a nightmare. Overall, thank you for the course. Despite those problems, I would still recommend it.

Tons of editing errors in lectures, and the programming problems rely more on knowledge of Keras (essentially untaught throughout the course) than they do on understanding of lecture material. A disgraceful end to an otherwise solid course sequence.

Keras is required to pass the assignments but no training provided for it. I can learn it myself of course but then the question is this - what am I paying for?

Poor submission system. Failed many times to upload and had to redo the assignments. I was using a 250Mbps high speed network. Also course materials are problematic. The instructors are not willing to fix the problems for many years.

Great module, I am lucky to have used this resources in learning sequence models, I can imagine running LSTM using one of the frameworks without ever implementing it myself, Andrew Ng/Deeplearning.ai is the best!

If not Internet, I would not have been able to study a world-class Deep Learning course at an affordable price. Thanks Andrew and team.

I think it is the best courses designed so far. Gives you exactly the appropriate amount of information needed to understand basics behind sequence models. A must do course for all the students who want to pursue a career in this field.

Professor Andrew is really knowledgeable. I learn a lot from his lecture videos.

I'm blown away by how quickly this series of courses brought me from thinking a neural network was a magic box full of fairy dust, to being able to understand even the (al)most complex of network architectures and what makes them tick at every level at a glance. A lot of time has obviously gone into structuring this course; not an ounce of fat present and the format of developing intuition before diving into the nitty gritty and optional further learning resonates with me on so many levels. Thank you Andrew Ng and the team at deepmind.ai and coursera!

I want to thank Andrew Ng and his team for the amazing work. You definitely make the world a better place sharing this knowledge, and it is an inspiration.

To the contents: the course covers many uses of sequence models, for many different formats (many-to-one, many-to-many...), the questionnaires are focused but comprehensive and the programming exercises cover a wide range of difficulty levels, from no-brainer-one-liners (most of them) to implementing LSTM backprop by hand (optional). They take away the dirty work from you but make sure you get how you would do it. At the end you get to work with pretty complex setups like the attention model, but you still get the feeling of knowing how it ticks from the very bottom up.

The actual merit is that, even if it feels simple, it actually does work and is a takeaway knowledge that can be directly applied for personal setups. And mr Ng's videos are a charm, you can totally feel the care. Glad to see him back after so many years :)

Cheers

I gave 5 stars to other courses in this series but this one doesn't deserve 5 stars. There were many typos and bugs in the assignments compared to the other courses of the specialization.

fairly more complex and deeper as previous courses. Nice ex. however.

To be completely honest, I loved Dr. Andrew's method of teaching. But the assignments just flew over my head because I didn't have enough hours of practice of Keras under my belt. I know Keras is there to make things easy but it's very difficult to just trying to pass the grader. To goal of assignments was fantastic, I mean, generating music, etc. sounds really amazing but I feel that if there was some more time given to make us better in Keras and other technicalities then I would've loved this course much more!

Exercises are sometimes vague and can be done without full understanding of the material. No officially given notes. No reading material that explains the concepts more clearly and in detail.

Very interesting course. it helps me a lot when trying to understanf sequence to sequence models.

Amazing content, can get really strenuous. An apt end to an excellent specialisation.

I really enjoyed the course!

Very interesting exercice and assignments from which a lot is to learn. Content quite complicated which will require from me to come back for review and deepen some points. Thank you !

Very easy explanation to complex algorithms.Loved the course

Excellent

Nice

Very interesting!!

A really joyful introduction in the Sequence Models, such as RNNs, LSTM etc. Sometimes the assignments got a little hard and with patience and help from forums, it gets achievable! Thanks again! :D

By far the most intuitive explanation of sequence models I have seen.