Great!

good

Good

Best

GREAT ONE. You will be getting better in some things thanks to this course, like object encapsulation , remembering fowar and back prop etc. I still want more freedom trying to use this tools in a challenging way. Like Kaggle does. Its too much info to get it right and know one is worth using. I woudnt change what there is, but I would add a final lab with a more open ended result.

The course is great for Tensorflow beginners. Unfortunately it provides only a superficial description of custom layers, covering only simplest one-line computations. Models covered in the course labs do not support summary() methods. I would like to know from the course how one would create full-fledged Tensorflow/Keras models that support all standard methods.

A good course to refresh the DL concepts in Tensorflow language. It is still a basic course so don't expect novel ML material from it. But it's good to understand TF code that you many encounter and convert PyTorch code into TF. Combined with other advanced DL theory, we can write TF code which creates complicated models.

One of the best course on custom Models and layers . As we all know importing a layer is an easier task it just includes a line but making our own models and layers is something which I always wanted to learn and I would like to say this course completely justified it

The course is overall very good and helpful to help me build my custom Model

Learn a lot of new concepts

But there are also lots of grading error

And I personally found # Your Code start Here# is annoying as I had to delete them first before I can code

Very good course which enables you to implement custom model structures, and custom training. I'll recommend the course if you are a researcher, student, or developer in need for trying modeling beyond already existing models, and keras api

A little bit too easy. It's too bad that the coding assigments are so easy and don't need any deep thinking...

Nevertheless it's a good course and the instructor explains very well !

Concise and simple, but I would liked to see more depth and more exploration. It touches only the bare ground and it is a really short course.

A little tedious course but overall a great one. I think after going through code some more times the concepts will seem fairly easy.

excellent and comprehensive course with enough examples to understand the concepts

detailed introduction of customization functionalities, could go a little deeper

some good stuff, but too short and pretty easy

Some material links were inaccessible

My opinion its good

Very nice course!

good course

good

The content is very clearly presented, but is very easy. Also miss a real-world challenging application exercise. All in all, too short, too easy for an "intermediate" level course.

For the last graded assignment, just keep the first and last layer. Otherwise, there will be a time off error

An interesting perspective, but the assignements modalities are a bit too easy.

I have a habit of reading course reviews before signing up for them. It helps me form an idea of its contents and decide whether to sign up and devote my time or not. I am seldom surprised much, but in the case of this course, I must admit I was amazed by the gap between the course rating and its content. I was aware, of course, of the 2-star review (by Irina G, posted on Nov 22, 2020) which, at that time, had by far the most votes: 18. The next most upvoted review (by Giora S, Jan 7, 2021) had 7 votes and it also gave only 3-stars. At that time, I was not alarmed by the fact that the most upvoted review giving 5 stars to the course had only 3 votes. Although it is somewhat surprising, I can understand that many people may feel good about a course just because it is easy to pass and, consequently, have a course like this have a rating of 4.9. But how does Coursera select top reviews with 5-stars and only very few upvotes is beyond me. This really makes me reconsider Coursera's rating system. I fully agree with Irina G's review. Could add few more observations of mine, but I do not see the point. I really appreciate the mission of Coursera, the effort made by the lecturers to prepare a course and the fact that we can listen to it for a comparatively very low price. But having Laurence read pre-written text from a screen with generic statements, explaining virtually nothing other than reading the code taken in large part from Keras tutorials which, at least, have explanations, is quite surprising. Even more so considering its rating is pumped up to 4.9.