This course felt rushed. Especially, the programming assignments, which had many errors and were frustrating at time. It is still worth it since the content is really good -- only if you are willing to go through the frustration during the programming exercises.

there are a lot of mistakes in programming assignments.

The lectures were great. Andrew is a wonderful teacher, but the assignments were beyond miserable. Jupyter notebook is probably the least stable, most infuriating piece of software that I've been forced to interact with. I spent countless hours trapped, not able to perform the most basic of operations, such as saving my work or submitting. I lost work innumerable times. I, like others, eventually resorted to "saving" my work by copying it into a text editor on my system for fear of Jupyter sabotaging me. Even if the system was stable, most of the assignments were worthless as learning experiences. The majority of "programming" boiled down to playing a cryptic game of fill in the blank. Bottom line, I wouldn't recommend this class to anyone in its current state. Especially as a paid service. I really expected better quality.

Unfortunately considerably a subpar course compared to the other four in the specialization. Programming assignment is a mess - wrong formulas presented, nowhere near enough Keras's tutorials, etc. Every assignment is passed by browsing the forum looking for help from other people. It is unclear to the point of being annoyed (got someone in the forum cancel his subscription). However, lectures are fine and sequence models cover a wide range of areas/applications, so you can't miss it anyway.

Many topics are only quickly skimmed over. Serves as an overly brief introduction to RNN.

Assignments don't match the quality of the other four courses of this specialization. Automatic grading accepts solutions despite results not matching expected results. This should be fixed.

If it could improve assignment accuracy, it will be better

some optional exercises are wrong, wasted a lot of time on LSTM backward propagation

There are a lot of mistakes in programming assignment. Please update and fix it

Videos are okay, but exercise is just debuging!

super unorganized!

really really bad

Professor Ng seems a little bit confused about the subject and is making unnecessary analogies rather than going deep into the algorithm and explaining the context as he did in Convolution Neural Networks course. I hope that the videos are revised and professor explains the topic more clearly rather than depicting himself to be confused as well on the topic.

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.

Excellent course. Highly recommended!

Excellent state of the art deep learning models made easy. Great job Andrew! And THANKS SO MUCH!!!

Auch der Letzte Kurs war sehr gut! Diese Spezialisierung hat sich sehr gelohnt. Der Stoff wurde gut erklärt und war sehr gut anwendbar.

cool

Thank you Andrew NG for teaching AI

Awesome conclusion to deep learning. The 1 side trigger detection algorithm is good final touch. Thank you Andrew NG..

Very detailed hands-on assignment. Hard tho

This was an awesome sequence. I wanted to understand Deep Learning and the techniques and ideas that had advanced the state of the art beyond ordinary neural nets. I was particularly interested in Sequence Models which are of interest in my line of work.

Andrew Ng at it best.

Best in the series

该门课程对序列模型的讲解由浅入深，一步步带领我们从最基础的RNN走到最后的LSTM及更复杂的模型，作业十分有趣，尤其是课程最后一次作业能让我们真切感受到深度学习的力量及其给我们的作业

As we proceeded with the lecture, we were able to gain a better understanding of the sequence model and further assist in envisioning entrepreneurial items. Thank you.