Excellent. Isn't Laurence just great! Fantastically deep knowledge, easy learning style, very practical presentation. And funny! A pure joy, highly relevant and extremely useful of course. Thank you!
Great course for anyone interested in NLP! This course focuses on practical learning instead of overburdening students with theory. Would recommend this to every NLP beginner/enthusiast out there!!
교육 기관: Hartger•
Overall the video material is fine. The assignments however are very unclear and contain bugs. The grader's test don't match the instructions. It's very frustrating that the assignments clearly haven't been given the same attention the rest of the course has been.
교육 기관: Prosenjit D•
This course is a far cry from Andrew Ng's deep learning specialization and refers to Sequence Models from that specialization at the drop of a hat. In short, no use doing this one, unless you have done sequence models (course 5) of deep learning specialization.
교육 기관: Dominik B•
No grader exercises,
sample code in the lectures isn't always updated and gives errors,
everything is a bit chaotic (eg order of sample code, sample code description, introduction to the topic is random; some random parts in the code).
교육 기관: Venkata S Y T•
The weekly exercises are not graded and the over all content quality of this course in comparison with the previous two in the specialization seems a bit poor and doesn't provide more learning on the topic.
교육 기관: Amit K•
Not clearly explained and only using toy and irrelevant datasets, nothing realtime industry specific examples. Also, voice quality is very bad for this course.
교육 기관: Jurica Š•
I would call this entry/beginner level material. There arent any graded coding challenges, which is a shame. No complex topics are covered with this class.
교육 기관: jack c•
It's a bit too basic and there are not many graded examples to work through like Andrew Ng's course. I feel it could have been more complete and in depth
교육 기관: Graham W•
Disappointing. Laurence much less able to explain NLP issues than CNN issues. Lots of problems with TF versions in Colabs wasted far too much time.
교육 기관: Joey Y•
The quality of the audio recording is worse than courses before. The questions at the end of the chapters are also repetitive.
교육 기관: Amr K•
didn't really feel like a strongly grasped the concept and needed more exercises also the lack of lessons notebooks.
교육 기관: Maged A•
Too short. Fine as introduction but not in depth course. No assignment except very shallow multiple choices tests.
교육 기관: Benoît Q•
Not enough content; far too easy; the whole course should be one week of a good tensorflow course.
교육 기관: Nirzari D•
The audio quality is very bad! It should be improved so the content is audible to the user
교육 기관: Anton Z•
I wish assignments were provided the same way as in the previous two courses
교육 기관: Masoud V•
Useful but shorter and easier than expected and not deep enough for me
교육 기관: Jose R•
It is too mechanical and reinforcement of concepts if very limited
교육 기관: Md. M R•
Good course. but we expected hands-on assignments to learn better
교육 기관: Alexander S•
Dont see the value behind predicting words.
교육 기관: AasaiAlangaram•
Not Much Information provided.
교육 기관: Daniel C•
Missing code evalution
교육 기관: Jack P•
Unfortunately, really disappointed with this course.
Having done the previous 2 courses int he specialisation I have come to realise that the courses are much more of a tutorial and could be seen as quick practice content before going for the TF Developer certificate or something. That in itself is fine, I feel there are other places to learn the maths/intuition behind DL (e.g. the Deep Learning Specialisation) but I feel especially in this 3rd course the content really doesn't justify paying for it.
For starters the explanations are very fast, hand wavy and don't go into any real depth other than just quickly explaining each line of the short notebooks (this can be useful). There is no discussion on how to improve the models or actually use this other than just pressing play in the notebook, the length of videos 17min per week is really not worth it, especially when better content can be found for free in Kaggle notebooks or on YouTube. There are also no graded exercises and after the first week they have given up on even providing suggested answers for the ungraded ones. The exercises don't test your TF understanding, just your basic Python loading of data and if you can copy from the example workbooks, they also have inconsistencies new untaught content and prone to errors that you haven't even been told could be an issue which means you just waste time being frustrated at not understanding what code you're even supposed to add rather than trying to understand the content.
I really like Coursera in general so this experience won't change that, but given that the instructor has free content on the TF website and youtube channel it seems like a waste to pay for this course IMO.
Hoping the 4th course will. be better
교육 기관: Huet P•
Videos are too short. Unlike Andrew did, there was not enough talk on intuition and how to tune the hyperparameters. There are a lot of redundant questions in the quizzes, and not enough explanations on the notebooks. I would prefer graded exams, not ungraded ones with answers. I would prefer the coursera lab instead of the google collab platform as we cannot access again previous works.
교육 기관: Alexander B•
Very little content. Extremely short videos, with some notebooks thrown in and show only the most basic applications... I would have expected in-depth explanation on Network-Architecutres, instead of having to memorize the name of some methods in keras (fit_on_text or fit_on_texts). Come on! This course seemed rushed, compared to the high standard of other deeplearning.ai courses.
교육 기관: Xiaotian Z•
Too shallow. The instructor spent too much time on some meaningless details and didn't explain some very important basic concepts nor dive any deeper. I hope this was taught by Andrew.
교육 기관: Nikolai N•
The lack of graded programming assignments is a big bummer