Sep 02, 2019
This is very intensive and wonderful course on CNN. No other course in the MOOC world can be compared to this course's capability of simplifying complex concepts and visualizing them to get intuition.
Jan 13, 2019
Great course for kickoff into the world of CNN's. Gives a nice overview of existing architectures and certain applications of CNN's as well as giving some solid background in how they work internally.
교육 기관: Yao F•
May 20, 2019
The course is pretty good with advanced techniques on computer vision. The only regret is one problem about the last coding homework. I failed to load the pre-trained model and can only finish the home work without checking the accuracy of designed examples.
교육 기관: Pankaj D•
Dec 26, 2017
Amazing course plan and delivery! Classic CNN architectures, ResNet, YOLO, face-recognition, neural-transfers - all in a very succinct package! Some very minor issues with auto-grading of assignments, but nothing that the discussion forums won't get you thru.
교육 기관: Jayaram R•
Jan 28, 2019
Andrew's explanations, and the exercises are absolutely fantastic. There seems to be a lot of tricky math in Convolution Neural Networks and Andrew's explanations and illustrations help students understand the essential concepts behind each type of Conv net.
교육 기관: Paul S•
Nov 29, 2018
Excellent course. Very good and well structured explanations by Andrew Ng: one concept per video, sometimes a second video to explain why the concept works or to give some intuition. Course covers many of the classis deep learning papers. Highly recommended.
교육 기관: Joshua P J•
Aug 07, 2018
Weeks 1 & 2 were very good. Week 4 was excellent with extremely clear presentation. I didn't like week 3; it felt like the topics were presented in random order, and the homework felt trivial (I finished it easily but I still have no idea what was going on).
교육 기관: Kaan A•
Jul 30, 2019
This course was the greatest one among the first 4 courses of the Deep Learning Specialization. Real world examples were perfect. Moreover, the paper suggestions helped me a lot to learn through my process of this course. Thank you Andrew and Coursera Team.
교육 기관: Michael G•
Nov 16, 2018
Great examples and walkthroughs. I didn't think I would be able to code all the various CNN architectures, but this course made that process challenging, but doable. Now it is time to start working on side projects to sharpen the skills I have learned here.
교육 기관: Artem P•
Apr 22, 2018
Probably the best course in the specialization (well, along with Sequence models). 50 layer VGG model built in Keras gives awesome enterprise-level results on a relatively small data sets..! But I recommend taking all these courses, they are all very good.
교육 기관: Guillaume G•
Nov 15, 2017
I really like how Andrew Ng is able to explain actually pretty complex concepts in a comprehensible way, built on the knowledge of the previous weeks content.
Also great is the integration of recent techniques: inception modules/networks, residual networks.
교육 기관: Amit A•
Dec 27, 2019
Excellent course. Professor Andrew Ng ensured easiness in following the courses, highlighted important aspects and the assignments were very well structured. I am glad to have taken up this course and I hope to start using my learning in the coming months
교육 기관: Daniel J D•
Jan 04, 2019
Andrew Ng's courses and Geoffrey Hinton's are about as good as courses get--rigorous, practical, and yet fairly thorough in the underlying theory. Convolution Neural Networks is certainly no exception to that as he goes into res nets and inception nets.
교육 기관: Yu G•
Nov 03, 2017
It's really a great course that I've waited for so long! Thanks a lot for providing the well-organized and easy -understanding materials for those new starters of deep learning like me! Hope to see the last part of sequence models in the nearly future!
교육 기관: Eric N•
Jan 21, 2018
The Neural Style Transfer assignment could benefit from some better descriptions and coding direction, but overall I loved all the assignments and learned a lot. I would like to learn more about Face Recognition and other Image Detection applications.
교육 기관: Sonny R•
Jul 30, 2019
This provide me with a much deeper understanding of CNN and the basic building blocks for building CNN and facial recognition. I really enjoyed the programing exercising and learning how to do leverage additional frameworks like TensorFlow and Keras.
교육 기관: Jack S•
Jul 21, 2019
Great course! I learned so many stuff. Andrew's lectures are very intuitive and helpful. Those Jupyter notebooks are definitely worth time exploring. One last thing is that I wish some limits of the current CNN model can be mentioned for big picture.
교육 기관: AMRICHE A A E•
May 03, 2019
Another great course in the Deep Learning specialization. It's been a wonderful experience diving into computer vision and discovering some exciting new applications and concepts.
Many thanks to the course team and a special thank you to Dr. Andrew Ng
교육 기관: Ratchainant T•
May 15, 2018
I really learn a lot from this course. However, It would be great if the course introduce how to annotate images and read annotated images to data set in order to get start computer vision project from scratch for audiences who has zero experiences
교육 기관: OL•
Apr 08, 2018
Great course which gives me a basic understanding on the technologies behind object detection, face recognition. Also, the programming assignments are very useful and give me hands on experience on how to build a basic system using the technologies.
교육 기관: Karan S•
Sep 05, 2019
The understanding of Deep Networks for Computer Vision gave me boost to go ahead and use them. I got some awareness about Keras, but I am a bit confused that should I stick with Tensorflow or with Keras. I Loved to work with Tensorflow in Course 2.
교육 기관: Bogdan G•
Mar 12, 2019
Excellent course on CNN which gets you familiar with many popular models from 2012-2016 including all the basic CNN models LeNet, AlexNet, VGG, Inception, ResNet, object localization/detection and YOLO, Face recognition with DeepFace, etc. Thanks!
교육 기관: Rahul K•
Aug 22, 2018
The best course among whole specialisation. One gets to learn a lot about image processing as well as a whole set of reading materials with every programming assignment. Go through the reading materials if you want in depth knowledge of some topic.
교육 기관: John P•
Nov 12, 2017
As always, Andrew Ng manages to make the relatively complex seem simple. The programming assignments are excellent for demonstrating some diverse applications of deep learning and the optional backprop for conv layers was particularly illuminating.
교육 기관: Bradley W•
Dec 20, 2017
Great course that gives insight in CNNs. The coding in frameworks is sometimes confusing and there were some bugs in the face recognition lab, but these are minor compared to the value of the course. Many ideas presented are state of the art.
교육 기관: Stephen M•
Jul 20, 2018
This was a really exciting course, presented in a way that was clear and is easy to understand. It is great that it uses such widely used frameworks such as TensorFlow and Keras — which will make the learning quite applicable to the real world.
교육 기관: Moaraj H•
Oct 23, 2018
It was good, but a few broken parts in the assignment almost made me quit. Once fixed it was the normal extremely useful, introduction into very cutting edge stuff. Thanks for putting in the work for this guys, it really is an amazing resource