Convolutional Neural Networks in TensorFlow

This course significantly lacks depth. The topic is covered at a very high-level and represents only a lightweight introduction. You will not gain any insights into the challenges that someone might face using CNNs on Tensorflow in a real-world scenario.This course does not compare to the kind of insights that you learn from the other courses taught by Andrew Ng.There are no graded programming assignments to validate what you have learned. The exercises that are provided are very simplistic.

You may look at it as a set of use-cases on how to work with particular types of .ipynb notebooks or how to structure your code, but, unfortunately, lectures are useless and tasks are mechanical rather than challenging. Huge disappointment.

This is the second course of the specialization and still I feel like I haven't been introduced to anything beyond the free tutorials available on tensorflow website. So far the specialization has also been only focused on the keras api of tensorflow which makes me feel that perhaps the name of this specialization has been poorly chosen (perhaps it should be 'Keras in Practice Specialization'). On the positive side, the instructor is eloquent and the learning material is presented in a well and orderly fashion (ignoring some minor cases of redundancy in notebooks; basically copy pasting the whole notebook several times just to introduce a few lines of new code).

I think I knew more about CNN before this course.

Excellent material superbly presented by world-class experts.Sorry if this sounds sycophantic, but this series contains some of the best courses I've encountered in50+ years of learning.

This is pretty simple. This doesn't give an idea of the real use of keras. also there is no programming assignments.

this course is very useful for beginners

It is a great intro but a very limited course. Short videos and a small number of examples, for example, Transfer learning could be more in-depth. Week 4 really made a few obvious changes in the code. I do think it's great material, but all of it could be made into a 2-week course instead. Thanks for your efforts.

Great course! I can't wait to going further and deeper. Thanks

Many thanks to Andrew Ng and team for the great balance of theoretical background, practical references and hands-on programming exercises.

It's a perfect course to learn TensorFlow for CNN, and it is extremely easy to understand. Thank you very much!

I enjoyed doing this course on CNN in Tensorflow. Thanks for the lectures by Laurence Moroney. And it is always a pleasure to hear Andrew Ng explain even difficult concepts in simple terms. He is one of my favorite teachers online, and reading about his ML course in a New York Times article back in 2012 or 2013 made me completely change my career direction and motivated me to eventually get into cloud and Big Data! And thanks also for the exercises on codelab. That makes it really convenient to learn and experiment with Machine Learning and Deep Learning. I did take the first course in the Deep Learning Specialization early last year, but didn't get a chance to do this until now. Looking forward to completing the remaining three courses sometime this year.