Very thorough treatment of Literature. Andrew goes in great length to describe basics of CNN and then goes on to show the applications.

Looking forward to RNN course.

este curso fue excelente, aprendí muchas cosas, en aprendizaje profundo, recomiendo el curso.

La explicación de Andrew es muy clara, y muchos ejemplos en los videos.

Great content with many examples and comprehensible videos. With clear reference to the original articles you can always look up more about the different algorithms.

great introduction to the topic. Lots of information and technique. This course enables me to converse with Machine Learning Engineers and help out on small projects

Fantastic course! I only wish the YOLO lectures and labs went more into detail about the implementation intricacies, such as the pre-processing of the anchor boxes.

Exceptional course with an in-depth analysis of all the CNN concepts you will ever face while working in the Industry. Thank you, Coursera for making this possible.

Very good in depth course about Convolutional Neural Networks !! Andrew Ng explains Convolutional Neural Networks from ground up to more sophisticated algorithms ;)

The best course for learning CNN , it guides you from basics like various steps of CNN untill making exciting project like face-recognition , NST, object detection.

Great Course for learning about Convolutional Neural Networks. The course content is derived from many research papers and a lot of insight is shared by Andrew N.G.

Some exercises may not clearly explain its aim and they might be better if we could engage more into the implementations.

Anyway, it is a course that worth to learn.

Awesome course. Andrew Ng is an excellent lecturer! I like the content, the explanations and the references in the course. Highly recommend this course to everyone!

Doing things in jupyter is easy. There should be atleast one assignment where you have to actually setup tf/keras with gpu in your system and use any high level api

great course on learning conv net, although the homework assignment is a bit too high level. but overall the concepts are very well presented. i enjoyed the course.

Another course which is clear in its communication, principles and objectives. Easy to follow, great examples, and exercises to reinforce what you have been taught

Andrew Ng and his team continue to impress with their ability to convey the topics and challenge you in the practical application. Well worth the time and effort!

Really helpful course with amazing and intuitive assignments providing hands on experience with deep learning algorithms for computer vision problems. Recommended.

The instructor has taken great efforts to design the course and explains really well. The assignment are well crafted to guide through the process of solving them

Course is onformative and useful. Still some concepts like why convolution do well for image data and YOLO algorithm are not clear enough. Thanks for this course.

This is the most challenging courses that I have taken on Coursera. Thanks Dr. Andrew Ng for giving the course and I benefited a lot throughout the whole process!

Nice course. Provides a good practical exposure to the concepts. Especially, the assignments were planned in a nice way to make the student understand the topics.

Truly a great course to give insight on Deep learning in Vision. The material is incredible and exponentially useful to start your career in this particular field

Awesome course, I learned a lot through this course. Thank you professor who helped me in understanding lectures and my peers who helped me in discussion forums:)

A fantastic convolutional neural networks course! Andrew Ng is a great tutor. I felt ready to implement my ideas on CNNs immediately after completing this course.

Another excellent course led by Andrew Ng. It neatly builds on the previous three and, again, strikes an excellent balance of difficulty and gentle encouragement.

One of the most fun courses I have taken. The YOLO model is the hardest part of this course, I still find it very hard to understand but I think is a genius idea.