The course is very good and has taught me the all the important concepts required to build a sequence model. The assignments are also very neatly and precisely designed for the real world application.
Learnt a lot about new concepts in RNN and LSTM. Really wanted to learn about these models. This course helped a lot. Everything was new and so fascinating. Loved this course and our teach Andrew NG.
por Octav I•
Great lectures, really well explained, assignments could request more from the trainee to devise the logic instead of having it already defined for him.
por Marcela H B•
Good course, however I would like to have more Transformers application in the last part as well as some information regarding the fine tuning of them.
por Thierry L•
Thank you very much for all the work you have done. I have learned so many things... I will try to use this stuff in the coming months. Yours, Thierry
por Tiago C G M•
The course is really good, I would recommend it to anyone who wants to learn the subject, but it lacks support from the staff in the discussion forums.
por Tomasz D•
Very good course. Some editing issues in the lectures and small issues with the programming exercises (outdated Keras instructions and documentation).
por Nicola P•
The lectures are excellent. The assignments are an extremely valid trace of significant deep learning application, while they lack a bit of challenge.
por Alon M•
As always, this course is great. however, for some reason this course is much more difficult then the others, and i feel as if it is packed too much.
por Michael S•
Really good course, like the others. A bit too black box in some of the programming exercises, so I expect to struggle when developing my own models.
por Yifan E X•
The videos are really informative and well structured. However, the exams felt like Keras tests. A detailed Keras tutorial would have been helpful.
por Takeo S•
It was great course,
I wish we have more speech recognition contents
Hope, you add new course a bit focus on audio/speech recognition etc
por Ara B•
too much content and not much chance to exercise. I will suggest for more frequently and smaller programming assignments through out the course!
por Rodrigo N S•
Outstanding course, but the end of it uses many architectures not fully explained (GRU and such). Incredible course and specialization, though!
por Reda M•
Excellent course, but I would have liked to work on predictive maintenance examples leveraging RNN and LSTM networks. Big thanks to whole team.
por Nishant B•
The course is nicely designed and every topic is explained in a very lucid manner by Andrew Ng. Must be done as a beginner in sequence models.
por Suraj S J•
Simplified content delivered in just the right way to give a perfect intuition of the complex concepts. Really enjoyed doing the whole course.
por Harry T•
Great content, but Andrew often starts his phrases then restarts saying them. Audio could use some cleanup, then this course would be perfect!
por Yunhua J•
Most optional assignments contain bugs/errors. Other than that, this is a great course, just as the 4 other courses in this specialist series.
I give 4 star because some fomulas are not correct! Though this course is really great. I can not understand why you made mistakes on fomulas.
por Makito K•
Great materials and programming exercises. The programing exercise in week 4 could be improved for the more beginner-friendly style probably.
por Rohit T•
This one seemed to go through to quickly over the details especially with the word vectors and the LSTM, would have appreciated more examples
por Joris D•
Very good course, though the assignments towards the end were a little too centered around Keras, which I personally don't care for very much
por Leung P L•
The instruction of using Keras in the programming assignment is unclear. There are many bugs as well, hence we have versions 1, 2 and 3 etc.
por Ruben Y Q•
No time series analysis, and some problems in the guidance of some programming tasks. Mainly de first week, the rest of it was pretty good.
por Jean-Michel C•
Good course. I would suggest to split the first week into 2 weeks, which makes easier to grasp all the concept with a deeper understanding.
Some assignments don't have enough descriptions to help me deeply understand the core concept of the algorithms. Hope it can be improved.