Great content

Very good!

The course offers a great introduction to TensorFlow methods for handling data, training models, and inferring results. Two things could be enhanced, in my opinion:

1) A better estimate of the time required to read the materials and do the exercises (the course takes less time than stated).

2) More in-depth explanations for certain parameters (although it could be argued that you should just follow the other deeplearning.ai specialisation for that).

Overall, though, a great crash-course for getting started with Tensorflow!

I took this course after taking deep learning ai CNN course. I found this course complement the other course really well.On itself, it is a little thin on theory size, but if you have already taken the other course, then this is a great consolidation of the material.

It take some time to change the code and run examples from this course with TensorFlow 2.0 locally on my computer. Today TF 2.0 is state of the art and required in practice. Please rewrite code for TensorFlow 2.0

More or less the course takes on Tensorflow's implementation of Keras rather than Tensorflow native env. It also only focuses on computer vision domain. Kind of misleading course title.

Learn a lot of tensorflow basics, which is good. However, the course is very short and easy to complete, and I cannot apply the neural network learned in this course to actual work

Ce cours balaye les fonctions de bases de la librairie d'abstraction Keras et permet de construire rapidement des réseaux de neurones complexes.

When each layer visualization was taught, I didnt get that part nor in the program. Else its a great starter course

It's relatively simple course if you've already finished Andrew Ng's deep learning specialization

Great introductory course to learn the application of TensorFlow with Keras.

Great course, but can be completed shortly instead of many weeks session

Amazing way of putting all the stuff together

Useful start for practitioner.

Good practice for coding on tf

The course is ok-ish, as are all the other courses in the specialization. This review is for all the courses in the specialization. I have a general shallow overview of DL but wanted to learn about TensorFlow and about Keras. For this it provides a good overview. You could learn it from tutorials too but at least I benefit from taking a course, as it motivates me to finish. But, the material is very shallow and it is a shame that there are close to no graded exercises. The quizzes are super easy. And there is no capstone project. If I didn't know the basics before I probably wouldn't have understood anything. If you know a bit of DL beforehand you can easily take one course per day. The fact that earning the certificates unfortunately degrades the value of it. If you finish in a month (and therefore only pay for a month) I think it is worth the price, even if what you learn is not that deep.

I think this is a great way to introduce NN to people that have never seen one.

But there was very little depth in this course. I finished the 4 weeks in an afternoon. The external references were at times way too advanced, while the exercise code was way too simple. That being said, the Jupyter notebooks were a great material and helped me start with NN really quickly. The MNIST dataset is brilliant and hank you for showing how to do it.

The reason why I gave 3 stars is because the MOOCs aI have done in the past were much more extensive and gave plenty of theoretical background. Some people might think that the lack of theory lowers the entry bar for students, but in my book that's a tutorial not a course.

Save yourself the $40 price tag and buy a book on the topic, there are plenty out there.

Material is very well explained and very relevant but the course is short in comparison to other deeplearning.ai courses before and could be richer both in content and in exercises (which are also not graded)

Instructors, please take a look at the discussion forum and answer some questions. It would save students a lot of time. The content of the course was overall awesome though.

Each video is a bit too short. And the assingment can't be smoothly finished and submitted due to environment issue. The creator should try to improve the user experience.

A very basic course, but it doesn't give you any fundamentals - just gives you a chance to recall keras API better. You'll be much better off doing cs231n, which is free!

The course was good enough on the high-level perspective but was expecting pure TensorFlow based implementation of the models instead of using the Keras high-level API.

The course was very basic but interesting. However, there were some issues when submitting the assignments. And the virtual lab uses tensorflow 1.x instead of 2.x

It's very introductory and the knowledge may not stick. I think it is more beneficial to take a full deep learning course with TF as an add-on to the course.

Great content, excellent explanations.

But I couldn't run the notebooks without running into kernel issues, the programming assignments were a real hassle.