Comentários e feedback de alunos de modelos de sequência da instituição deeplearning.ai

Thank you for this wonderful sequence of courses! This whole concept is still a bit blurry for me, but as a lot of people during the interview have mentioned, one must simply exercise new skills to understand the technology.

It's great course to get concepts right and overview. It will be great if you add further programming assignments(other than partially coded ones) or resources as such where one can practice what he had learned as optional.

Great choice of material, i would be happy to have one more week of that course to see more examples and have more time to familiarise with the concepts. All weeks were very useful and all the material was greatly explained.

I enjoyed all the courses of the specialization but I was looking forward to Sequence Models the most. I think a lot has been covered in this course and I can't wait to try working on projects with the knowledge I now have.

This course is good , I learn RNN,LSTM,GRU etc.Just one thing, the last assignment is hard to submit.I guess maybe there is a systematic problem that need to be solved. Everything except that is great. Thanks a lot, Andrew.

This is an excellent course for a beginner like myself. I would like to thank Andrew for making this course available to everybody in the world. Thank you so much for your inspiring course. With best regards, Seungbum Hong.

This course has helped me in developing an understanding for implementing sequence models through Recurrent Neural Networks that can be used in number of applications such as Natural Language Processing and Audio detection.

A briefly introduction of Sequence Models to solve sequence problem, such as translation, speech reorganization..etc. Homework is also very helpful to understand what is going on step by step under Recurrent Neural Network.

This is an excellence training course! I had a wonderful experience learning the leading edge Artificial Intelligence knowledge specialized with Deep Learning and believe this will make a life-long impact to my career path!

Excellent Course! The maths and concepts were a bit tough to understand and I had to look up some(a lot) of stuff but the learning experience and the thrill of actualling building and training the model is very satisfying

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My favorite by far, and I'm not a fan on NLP. Sequence Models, especially attention mechanisms seem to have so much potential. Interested in using them to look at time series data analytics for industrial iot applications.

Excellent Course by Professor Andrew NG, I enjoyed learning what lays under the concept of Deep Learning and Neural Networks.

Thank you very much to Andrew Bg and the team, and as well the mentors supporting the students.

The course content is great overall! The only thing I am a little unhappy is that one or two of the programming exercises have confusion instructions. But finally I made it under the help of peers on the discussion forum.

RNN model was quite difficult for me to learn, but all these lecture videos and programming assignments helped me understand it better. I liked the "Trigger word detection" (the last assignment of this course) very much.

Absolutely fantastic course! Perfectly follows on from the Machine Learning course by Prof Ng et al.

(One slight issue with some videos' audio: there was a very high-pitch whistling that was almost painful to the ear.)

At first I thought this was the least interesting course, but after the lectures and labs I have to say that this is really the most interesting of them all. However it requires some knowledge from the previous courses.

The final course was very brief and bit harder to digest. The assignments and quiz where also tricky but, overall had fun. Thanks Andrew Ng and team for the Deep Learning Specialization course to be offered on Coursera.

Out of all five specialization courses, this was second most useful (right after first course in the series). Also one of the few that used any modern DL framework (Keras) and not implementing pseudo solutions in numpy.

I was able to understand the difference between sequence models and previous course models. Moreover, I understood now how text and speech can be processed by AI. Finally, I could understand better the Keras framework.

This was an excellent course. The materials were perfectly structured to maximize understanding. I had no idea of a RNN and the course made a fantastic job in explaining and helping me develop a precise understanding.

Yet again Andrew Ng explains complex topics related to Sequential models in a much easier and understandable way . Barring few problems with the assignments and missing overview on Keras , overall course is a good one

F​antastic course. I benefitted immensely from Professor Ng's easy-to-understand lecture videos and the practical programming assignments. Looking forward to taking more courses from Professor Ng and DeepLearning.AI!

This Is very helpful course in order to learn Recurrent Neural Networks. The first 2 weeks were amazing but the third week was a bit less interesting. This whole series of Deep Learning Specialisation is really good.

firstly, I know about RNN is from this course, the explanation is clear, combination between theory and practical is great. This is a good resource for you if you want to know about RNN, NLP with Deep Neural Network.

Thank you! Although I have been working on AI for more than a year, coursera has given me a more systematic understanding of my previous work, and many opinions have been very helpful to my work, thank you very much!