It was a great specialization and a great course, thank you so much for giving me the opportunity to learn from you special thanks to Dr. Andrew Ng for his exemplary efforts and for teaching the greatest courses of the machine learning technology, I'm really proud of myself for finishing that specialization and I'm so grateful for all of you. Thank you ,Coursera.

Very clear delivery of material and lots of tips for real world applications. Appreciate the hard work that Andrew and everyone who contributed to the course material and mentors on preparing an amazing specialization. Machine learning is not the most straightforward subject to learn and having such a well structured course goes a long way in getting us started.

The whole specialization is excellent. I highly recommend doing it. The only minor comment that I add is that Andrew should include some links for further reading (along the courses for each topic or theme). I know that anyone can quickly look up for them in the Internet (and they can be outdated) but that would make the specialization even better in my opinion.

This is Course 5 of the Deep Learning Specialization, and the last one. We learn Recurrent Neural Network (RNN) /Sequence Model, which allow translation or trigger word (like "Hey Siri!"). It's a completely different beast than CNN seen in Course 4. Again, nice videos and explanations, and well-designed useful programming assignment (TensorFlow/Keras and numpy)

I Highly recommended this course on Sequence Models. The course is easy to follow as it gradually moves from the basics to more advanced topics, building gradually. Andrew Sir makes the cocepts behind the scenes about LSTM GRU etc very easy to understand. Assignments are great, extremely well designed. Best assignments you will ever get to practise and learn.

The kind of simplicity with which the course is explained and the amount of knowledge gained is worth the hard work of many months! . . I would like to thank the whole Coursera team and Sir Andrew Ng for creating such a wonderful platform and a big shout-out to all the mentors and community who have replied to the most basic queries in the discussion section.

Home work assignment notebook has a quick time out issue. It's quite annoying since most of the assignment has lots reading material to fully understand the topic or method. Often the notebook just time out and has to be restarted before move to the next section. Hopefully, it can be fixed or improved.

Overall a very good course to learn about sequence model.

This was truly an exceptional course on neural networks. Although created several years ago, i havent seen a better course on coursera yet. The course went through all aspects of all types of neural networks, was very detailed and explanatory, apart from the last week of the last course - transformers work. Highly advised for all machine learning engineers.

It took me a longer time to finish the course due to busy schedule. But I found it totally worth the struggle to work on the course material. Sequence modeling and processing is an new area to me. The course taught me some basic concepts and gave me a chance to lay hands on through programming exercises. I feel a lot like the topic particularly NLP. Thanks!

Très largement plus difficile que tout ce qu'il y a eu auparavant. Un véritable apprentissage et un plaisir surtout sur le Trigger Word Detection qui était très intéressant.

Totally more difficult than anything before. I've acquired true knowledge that I'm very proud of. It was a pleasure, especially for the Trigger Word Detection which was very interesting.

Exercises too basic. Better to do something simpler from scratch, them fill in the blanks on statements like "define a to be a boolean variable initialized to True", and run a bunch of other cells with imported code that hides the actual complexity. These kind of exercises does not add anything to the student. Content of Andrew's lessons is great, however.

This course helped get a good intuition as well as further specifics of voice recognition which is what I am most curious about.

I think they have put together a right mix of Conceptual puzzles, Implementable codes and Lucid lectures to help one learn and advance one's understanding and intuition framework to build on top of subsequently.

Great work guys!

This course provideed a good introduction to sequence models and deepened my understanding about RNNs, LSTMs and Transformer networks. The programing exercises helped improve my understanding of the concepts introduced in the lectures, and some of them were also very fun to implement and see how sequence models can be used in real-world applications.

Thank you Prof Andrew Ng for sharing the knowledge and experience. It has been truly a great learning during the course specialization. And I always admire the way you structure the course and teach the advanced concepts with such an ease. With the power of AI, we as a community try to solve real-world challenges for better life. Thank you so much!

awesome! Thanks to Andrew and his time to deliver this wonderful course. It really give me a very good sense about what's going on with the Deep Learning in several areas. The course material is prepared in a way that it's very easy to catch up. Just one suggestion, this sequence model session is too short, lots of topics haven't got well deployed.

Very very interesting but it's a lot more difficult than the other courses. I did it out of sequence (no pun intended) (i.e. I skipped Convolutional networks to go straight to RNN, because they interest me more).

That wasn't the correct move. I barely knew anything about Keras, the exercises took a LOT more time. Still, it's a wonderful course.

The class lectures are easy to follow and programming practices showcase a good variety of interesting implementation/practice of sequence models. Not only does it introduce how models work and are constructed but also illustrate how those models can be applied to real-life problems (e.g. voice detection in smart home, music generation...etc.,).

I have earlier completed first 3 courses of the Deep Learning Specialization. This course widens the horizon of deep learning applications. Through the assignments, I have gained confidence in understanding the model architecture and the underlying theory behind it. I recommend every to enroll for this course if they want to learn how RNN works.

Great lectures on the intuitions behind RNN and their applications in real life. It requires some self-exploration to complete the programming assignments related to Keras and tensor, but the structure of the assignment is very good. I have learned a lot from this lecture and it helped me to understand the language of the field of deep learning.

Awesome course, with lot of detailed and well guided practices! After finishing all of them I went directly to look on GANs and Transformers and with the knowledge gain thanks to Andrew Ng and his team, I set up my local Jupyter with tensorflow-gpu and start using state-of-the-art machine learning! Check out paperswithcode for awesome projects!

I decided to do this course after reading the first few pages of the Deep Learning book by Goodfellow, Bengio and Courville. I'll probably go back to that book now, to reinforce what I learnt from this set of 5 courses. I plan to also get more practice with the programming frameworks. The Tensorflow specialization is probably my next conquest.

This course is really fantastic. It teaches several of the most important contemporary applications of deep learning, and mentions lots of important points of these models.

The assignments are amazing. They are easy but still able to make sure you've gone through the whole design of models.

Definitely one of the best lectures I had in my life.

Many thanks to Professor Ng, this is absolutely the best online course that I've taken. It is fantastic how much value he creates for all of the learners, conveying very complex ideas from the world of deep learning in a simple and understandable way. I hope one day I will meet Professor Ng and thank him in person. An amazing specialization!

Finally, after 6 months achieved desired goal in Deep Learning Specialization.

Thanks to #andrewng #coursera team for motivation and opportunity. It was not possible but due to #andrewng motivational words and explained deep knowledge in simple words. I can't express my feeling in words. Thanks again

Best wishes for Andrew Ng and Coursera Team

Excellent as always. This subjectcould easily take more weeks or even months to understand, but Andrew explains complicated concepts in very easy terms. Though sometimes it seems a bit esoteric and magical, due to how easy he makes it sound, it's a great start point to begin to investigate, read and implement the most important algorithms.