So exiting to learn about face recognition algorithms and entering the world of computer vision. I'm greatful for being able to understand a little bit more about convolutional NN.

The course content was perfectly curated and delivered for a beginner. I now have a better understanding about Convolutional Neural Networks and its applications in various fields.

Fantastic! As with any course, there is a line between "spoon-feeding" and "you work it out" and I think this course does mostly wonderfully here, minus a few maths here and there.

So far this has been the most challenging course in this specialization. However, Professor Ng's lectures are always exceptionally well planned and the order is absolutely spot on.

It was awesome to gain intuition about how defining custom loss functions can be used in very creative ways (ie. Style Transfer and Face Recognition). Highly recommend this course!

Loved the course, but the Week 4 exercises contained lots of bugs (had to search through the forum for workarounds) and the notebook server kept crashing - cost me a lot of nerves.

I feel that the programming assignments can be covered in detail during the lecture, especially segments that do not require our input, to get a better feel of the entire exercise

In-depth analysis of core concepts of CNNs, exciting programming assignments and great support from the community mentors. Another high-quality course by Andew and his colleagues.

A bit mor etheory would have been welcome.I think especially about the mobileNet and the notion of "network in network"which seem to be interesting directions of exploration.

This course is very interesting, it helped me grasp the current trends in deep learning and computer vision. Andrew and his team have prepared some high quality learning material.

I could not understand how many times I try to understand the convolutional neural networks by reading books, but Andrew made me understand it with this course just going through!

A was so confused about CNN, had done many other courses. but didn't get the actual knowledge behind it. But after this course literally I get to know almost everything about CNN.

This course was great....Gives a real concept of realtime face recognition. And this has realatively less mathematical eqns than the previous course. It's also easy to understand.

Great course, well explained, programming assignments are interesting. I liked the active forum community which lacks in so many other courses, with mentors also giving hints etc.

Awesome course!

When reading papers and trying to understand, it takes quite a lot of time.

However, this course is very friendly about teaching the core concepts within the papers.

Great content with a lot of programming exercises (big plus).

It would be nicer if it can go more depth on how those well-trained models has obtained their parameters in practice.

Perfect. This course has details and knowledge we want. Some advice for the class: if the ppt could be download, that will be much better. And also some summary ppt could be added

As always, Andrew gives a clear cut and concise introduction to a very conceptually challenging topic.

This course, like all his others, is top quality. Buy it, learn it, use it!!

Great fourth course of this great specialization! The explanations are clear and you get a lot of knowlegde from scratch about Convolutional Network. This course is really useful

Thanks for the amazing explainations, intuitions and wonderful tutorials, all tricks and tips to begin the course with. You guys really worked hard to make the course meaningful.

The course was extensive and covered the mathematical aspects of convolutions.The architecture and outputs at every layer of a CNN was thoroughly discussed and explained clearly.

One of the best courses I have done so far. Anyone who wants to learn all the basic concepts can do this course. Also, it has some really good assignments and applications of cnn

Excellent Course - What i really appreciated was Andrew's insights into what the Convolutional Networks are doing and the rationale for some of the popular network architectures.

Отличный вводный курс по сверточным нейронным сетям. Даёт понимание основных принципов и уверенность при дальнейшем самостоятельном изучении. Курс довольно прост для прохождения.

Nunpy basics should have been covered in detail as calculus was covered in deep neural networks since is being heavily used in this course .1 Hour coverage would be excellent !!