This was the most difficult course I did in this specialization, but I loved it, I loved it very much. Thank you very much dr. Andrew and coursera for the opportunity, I really understand the importance of studying computer vision and this course was very useful in this journey. Thank you very much, I really loved ...

The last 2 courses were delayed, but the positive side for me is that, in the beginning I proceed too fast and didn't learn that well, the delay made me take more time on such a valuable course, carefully reading and memorizing the instructions of assignments. I'm really grateful for Prof. Ng's excellent instructions.

I completed the entire specialization and having nothing but good things to say. Highly recommend it! Lectures are engaging, and Andrew does a fantastic job explaining some very complex topics. Programming assignments are challenging in a good way. You’ll really feel like you’ve learned a lot by the time you’re done.

This Course was exceptional and upto mark. I learnt a lot of stuff easily and was able to implement into the real world example. This was really helpful for building up my resume. I thank Andrew Ng and Coursera team for giving financial aid to take up this course. The amount of knowledge gained is so valuable to me.

Awesome. This course was much more dense than the other ones, there is so many areas to review. Since this course is about my favorite subject, I will need to pause and rework on each individual points and associated papers (yolo, nst, similarity learning) which will probably take me weeks... Prof Andrew is the best

I thoroughly enjoyed taking this course. Beautifully designed...Thank you!

I had written a detailed review of the first 3 deeplearing.ai courses at : https://medium.com/towards-data-science/thoughts-after-taking-the-deeplearning-ai-courses-8568f132153

I will review this CNN course as well, in the form of a blog post.

Great course, provided many clear explanations I has been searching before. The one thing they could improve is that some of the practical exercises seem more focused in the framework than the algorithms. (I spent more time googling how to pass parameters to specific functions than actually using the algorithms)

Good amount of challenge for after work learning. Nice exposure to different applications of AI. Fun.

Andrew Ng is awesome at explaining the concepts. Almost anybody would be able to understand them after he presents them. I also appreciate how genuine he is. You can trust that there is merit to what he tells you.

Another excellent course. Convolutional Neural Networks is no longer a mystery. I like the fact that Andrew doesn't teach this as an academic class but has a very practical approach that can be applied right way. He lets you know the strengths and weakness of each of the NN and gives his personal opinion as well.

It is a great course that covers most part of Convolutional Neural Networks. I have learned a lot from it. Thanks Andrew! Only one suggestion: we have learned dropout and the batch norm in previous courses. Because they are such important tricks, it would be better if you could cover how they can be used in CNN.

Greatest cores for me till now on deep learning. I recommend it for deep learner or computer vision student. The best thing in this course is that it is very practical and up to date, and full of research papers of algorithms that Google and Facebook currently uses. Thanks a lot Prof Andrew Ng you are the best.

What a ride! I am not even very much into Deep Computer Vision, but this course made me finally understand how tensors algebra works and how they flow in the network. Andrew is just able to put it in so simple terms and in a very accessible way that just for that the course is already very remarkable! Congrats!

An Excellent Course to make people understand Convolutional Neural Networks in good depth and with ease. The detailed understanding of the major Convolutional models like YOLO and ResNet is like an icing on the cake. I would like to thank Professor Andrew N.G. and his team for developing this wonderful course.

Muy bueno para empezar a entender los conceptos de las capas convolucionales. Luego muestra modelos profundos como AlexNet, VGG16, ResNET, Inception que se pueden entrenar usando transfer learning. La parte de detección de objetos es la mas complicada. La parte que más me gusto fue la de reconocimiento facial.

The intuition and examples made this course easy to understand and learn. I loved how Andrew decomposed current published papers into an easy to understand format. All of the important points to remember were highlighted without wasting time on the minutia. Thanks for all the hard work put into the course.

I enjoyed a lot in this course...who wants to know how to build the CNN model...then this course is absolutely for them..they should try 100% this course. this course gives u insights into how to build your CNN model this one is I think the best course for that...thank u sir for this type of good content...

Nice exploration of CNN theory covering theory and Python exercises through different algorithms. One recommendation would be update broken links and re-write comments in code as sometimes it is not clear what variable or what is needed to complete the required functionality, specially on ungraded exercises

This course explains the details of CNNs with a great simplicity. It also presents some state of the art CNN architectures with their ideas very clearly. Finally the assignments allow to implement several CNNs and also show how transfer learning is used to perform face recognition and neural style transfer.

One of the most important courses in the Deep Learning Specialization in my opinion. Good content, enjoyed the homework, lots of details for beginners and extra resources for more advance content. Would definitely recommend for anyone interested in working in Machine Learning especially in Computer Vision.

Exceptional Course. Learnt a lot from it. Takes a different approach to teaching than other courses in the sense that more focus is on applications rather than training of models for which a GPU cluster is a must. Thanks Andrew Ng and his team for the wonderful course. Looking forward to sequence models :)

This is the course I enjoyed the most among the Deep Learning Specialization Course threads. Seems very practical to me and I learned a lot about CNN. A few more detailed practice in notebook problems could've made things more interesting. Many thanks to Andrew Ng for making such wonderful lecture videos.

An amazing course to get an advance knowlege and practise "Convolutional Neural Networks". Andrew Sir makes the math and concepts behind the scenes very easy to understand. The course is easy to follow as it gradually moves from the basics to more advanced topics, building gradually.

Highly recommended.

Professor Andrew is really knowledgeable. The lecture videos he makes are really helpful for me. I really learn a lot from them. Also, the recommended learning materials such as academic paper he recommend are really useful for me if I want to further my learning on the residual network or YOLO algorithm.

Fascinating course, as usual Prof. Ng gives fantastic explanations and breaks it all down into easy to understand fragments. His style is really engaging and he is so encouraging. There are some amazing applications in the programming examples that you'll want to play with long after the course is over.

Great course by Prof Ng. I had taken his Machine Learning course a few years ago, so expected high standards of content and assignment preparation - I was not disappointed. Staff is very responsive and helpful in forums as well. I highly recommend it. Taken as part of the DeepLearning specialization.