one of the excellent courses in deep learning. As stated its advanced and enjoyed a lot in solving the assignments. looking forward for more such courses especially in Natural language processing
A very good course and it is truly insightful. This course deals with more on the concepts therefore I have a better understanding of what is really happening when I build deep learning models.
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The material that it is trying to cover is very good. The programming assignments are intuitive with fill in the blanks kind of approach. Finishing them and the quizzes was a breeze.
But if you are new to tensorflow and Keras and a picky like me in wanting to know exactly what is going on and how, this course is wanting details.
It does have few other minor hitches -
-It has missing links to resources (you can dig them out though)
-mistakes in slides (that they embarrassingly correct inside)
-If you care about math, it might be disappointing when you see formulae with ill-defined variables and assumptions about notations that are not discussed. If you have a background, and do simple web search you will find it out in no time though.
By Bikhyat A•
The course is really awesome, especially the lecturer Andrei Zimovnonv's lectures are really good. His flow, the concepts he provide, all are lucid. However, Alexander Panin's lectures are, I think quit difficult to understand. Most of the times, he suddenly delivers so fast that you can't even hear what he actually said. I think, he should work on that. And honestly, I still have lot's of confusion in the portions he covered i.e. embedding, auto-encoders, adversial networks etc. One more thing what I'd like to add is, the instructions provided in the assignment notebooks are sometime very hard to understand making me feel they're confusing and incomplete.
By Arend Z•
Very helpful to get a good basic understanding of the different types of neural networks and their application. After finishing the course, I do not yet feel confident enough to build my own neural network applications. Maybe this can be solved by having more programming assignments at 'beginner' level, before 'stepping up' the complexity.
The provided 'example' codes - that work after successful completion - serve as a good starting point to build your own neural networks.
By Anselmo F•
Very interesting course, the notebooks are very useful and all the concepts are very well motivated and explained. I just found some bugs in the course and had some problems with the explanations of week 4 and I believe week 5 lacked the explanation of some basic concepts, but all of these gaps could be filled with a research of additional material. Anyway, I recommend this even for beginners, all you need to know are derivatives and some Python basics.
By Abhinav S•
It is not an easy course, but the course projects are very nice. I really liked the RNN and CNN parts of this course very well explained and had some rigour to it.
My only complaint about the course is that it is not self contained. You will have to read up a lot more and refer to other sources on the internet to get a firm grasp of what is being taught and then go ahead to tackle the exercises.