Comentários e feedback de alunos de Sequence Models da instituição deeplearning.ai

The best introduction to NLP and RNNs. Andrew Ng is simply remarkable and the assignments were interesting too. Highly recommend it for others. Felt a tad nostalgic as this was the final course of the specialization - Andrew Ng has that effect on you.

It was a great experience!! I have completed my entire module of Deep Learning. I am now good to go with Deep Learning. Wish me luck!! Thanks a lot, Andrew Ng and team for creating this beautiful journey!! I hope you spread this knowledge everywhere.

This course, as always, de-mystifies a quite complicated topic and gives very good intuition why the models work. For example, LSTM is very complicated unit but Andrew illustrates well what it tries to achieve. That said, this is a very tough course.

This course is one of the best course we can take for deep learning.The quiz assignment was good.The programming assignment was easy to understand many functions which i find it difficult in videos.Overall the instructor Andrew Ng lecture was good

This course covers a lot of ground and provides many opportunities to practice the concepts. I just wish there were one or two (possibly optional/honors ) assignments with fewer walk through instructions so one could test one's learning for real.

This was very cool, RNNs seem very powerful. I don't think the programming exercises were the best to get some experience but I really like the way Andrew explains the algorithms. Still 5*

(They are totally using these reviews for text analysis :P)

This course is a nice introduction to neural networks applied to sequence models. It has interesting applications in natural language processing and speech recognition. It would have been nice to apply the concepts to time series prediction, too.

This is a pretty cool course to work on introduction of NLP. A blend of practical and theoritical aspects included though there are black boxes (I felt Convolutional Course to be more effective though, maybe because of my background, but still!!)

I don't know why this course has not been rated more than the other courses of this specialization. In my opinion, this is the best course among all the others. All thanks to Andrew Sir and Coursera team to introduce me to this specialization.

The course is very helpful in learning the important concepts of RNN in a very easy way. The instructor has a very unique style of teaching which makes the typical concepts easy and at the same the makes you develop your interest in the course.

Andrew Ng and the team have created a fantastic opportunity to learn the basics of Deep Learning Algorithms. "Hearing from Lion's mouth" was a great experience for me. I would strongly recommend any deep learning enthusiast to attend the course.

somewhere between 4 and 5 stars. It's a good course to make you understand about major knowledge to process sequence by DL, and the assignments are the hidden gems.

Some recent results are not included (of course), such as BERT. But it's till OK.

Great course teaching state-of-the art NLP technologies. I wish the attention notebook could be improved, and the projects could get more flexible and in-depth. I also wish there could be a Keras tutorial that gives an overview of the framework.

Andrew Ng is a fantastic instructor. His ability to break down a complicated concept like neural networks and deep learning so that a non-math, non computer person like me actually understands the underlying mechanisms is quite extraordinary.

I think the course and specialization are special. It requires a lot of hours to finish it. It can be a great review of specific topics in the deep learning subject. Thank you for allowing us to reach those specific topics easily. Great content

The course explains the fundamentals of RNNs, GRUs, and LSTMs in a very easy manner with plenty of illustrations and programming exercises. Although, some of the exercises are optional but doing those actually help reinforce essential concepts.

Très intéressant. Les papiers scientifiques illustrés dans les travaux pratiques sont récents et cela fait plaisir de comprendre comment marchent ces réseaux de neurones de notre quotidien (traduction google, trigger word, style transfert, ...)

State-of-the-art and in-depth content, inspiring and engaging lectures throughout the whole specialisation. I will be eternally grateful to all of you who created this (and the other) courses. Thank you, Coursera, thank you so much, Andrew Ng!

Very useful for understanding what 'sequential' means in DL. I expected as some new solution to the time series scenarios but it turns out a different area from the quantative techniques. It might be helpful applied to more 'sequential' areas.

Yes, I have just finished the whole specialization. I'm very proud of myself. And I recommend this specialization to anyone who wants to start with this field. Andrew is the best one I've seen who able to explain the thing in deeper way. Thanx

A wonderful, intellectual experience!

Don't fret if you are having to look up a few documentations, the comprehensive documentations of the built-in functions/layers needed are accessible on the official websites of the libraries(Keras, NumPy).

"I think that every person whether you come from a wealthy family, or a low income family, or anywhere in between. I think everyone should have great opportunities. " (socioeconomic status)

I was shocked by this speech. Thanks to Prof. andrew

The course was brilliant! Even though, the programming assignments could be better (personal opinion). The teaching itself is brilliant, and I think Andrew NG is by far one of the best Deep Learning teachers for anyone looking to get started.

very nice course but bit comprehensive especially Sequence models.

Expecting a same comprehensive course in Python development also so we can not write just a piece of code but entire code.

Also expecting a course on Keras , and end to end one.

More lectures are needed in the sequence models to make these models or ideas clear to deep learning learners. I found this course is the most difficult one to follow in this series even if I got quite a lot experience on time series topics.