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Learner Reviews & Feedback for Convolutional Neural Networks by DeepLearning.AI

4.9
stars
36,530 ratings
4,731 reviews

About the Course

This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applications ranging from safe autonomous driving, to accurate face recognition, to automatic reading of radiology images. You will: - Understand how to build a convolutional neural network, including recent variations such as residual networks. - Know how to apply convolutional networks to visual detection and recognition tasks. - Know to use neural style transfer to generate art. - Be able to apply these algorithms to a variety of image, video, and other 2D or 3D data. This is the fourth course of the Deep Learning Specialization....

Top reviews

AR

Jul 12, 2020

I really enjoyed this course, it would be awesome to see al least one training example using GPU (maybe in Google Colab since not everyone owns one) so we could train the deepest networks from scratch

RK

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.

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4451 - 4475 of 4,686 Reviews for Convolutional Neural Networks

By Achille H

Jul 06, 2020

Great content, veerything is clear and concise. Only downside is the grading of the exercises, which sometimes requires you to use a very specific syntax (even though another syntax gives the exact same results) and causes hours of painful debugging and reading through the forums.

By Patrick C N

Feb 02, 2020

Model implementation is abstracted in many exercises. Many helper functions are created to just make things work. TensorFlow feels a little foreign still, not enough of an overview. Higher level APIs like Keras and/or PyTorch might do better here instead of mixing in TF randomly

By Cristina B

Feb 07, 2018

The last two weeks sometimes bored me and sometimes I had hard time in doing the assignments. The intuition behin object detection/face recognition and neural style transfer are well explained, but some more details for understaing how these models work is missing in my opinion.

By ALEXEY P

Jun 28, 2019

The lecture content is good but the programming exercises are not explained well. Quite often you are left on your own to go through Keras and TensorFlow documentation. So, don't expect much help in learning how to implement the theoretical ideas explained in lectures.

By Richard S Z

Apr 27, 2018

The lectures are very good. The programming assignments are sometimes infuriating and do not add to an understanding of the subject at hand. More can be done to explain the Tensorflow and Keras code. Also complete code explained line by line would be VERY helpful.

By John

Jun 26, 2018

I learnt a lot in this course, but i have the feeling that my knowledge is still very shallow specially when it comes to convolutional neural network design, i cannot tell pros and cons of each design and how to come up with new design that meets my use case.

By Linying M

Feb 22, 2018

The course is really good, but the assignment grader is a disaster. I spent days and nights reverse-engineering the expected codes, read the forums, only to pass the course before subscription expires, and this is certainly a very disappointing experience.

By Dushyant K

Jul 15, 2019

I wanted to give five star; however, I could not. The function "model_nn" in Week-4. assignment -1 has been very poorly designed/ poorly explained. When I searched the forum, there are numerous questions on the same topic; but,, there was helpful hint.

By sambit m

Jun 01, 2019

Bugs in the template code cause a lot of time waste.

Also, the exercises need to be better which teach how to actually build a model ground up rather than just filling in small parts.

Getting the main models working is the key, which is not covered here.

By Max S

Jan 12, 2018

A great course, but I can't give it 5 stars... There's just too many broken assignments, the videos are barely edited, staff completely ignores discussion forums, and it generally feels a little unpolished. I'm sure this will improve in the future.

By Ankit J

Sep 12, 2020

Videos are great and give a strong understanding of the concepts, but the programming exercises are underwhelming. I don't particularly feel confident about the hands-on understanding of the concepts after complete the somewhat shallow exercises.

By JiahuiWEI

Mar 14, 2019

Improve the quality of vedio please. there are too much repeats that could be easily avoided, it much worse than the first two courses, not about the centent, but the vedio itself, is your workers seriously correct the probleme of vedio??????

By Deep M

Aug 12, 2020

The course was great but only the first two weeks were sufficient for me as a Mechanical Engineer. I am not really interested in localisation and face recognition. Also, high time that you should update to Tensorflow 2.0 for your exercises.

By Marco K

Feb 17, 2018

What I really liked about the course was the actuality of the paper. However, I would have thought it absolutely necessary to explain the BackProp for CNNs. Also the grader problems in the last assignment force me to subtract two stars.

By Francesco B

Nov 30, 2017

Face recognition notebook has a bug, I passed the grader but the function triplet_loss returned the wrong value in the notebook. Several other people have had this problem despite the fact that the notebook was supposed to be updated.

By A O

May 22, 2020

Assignments do suck.

If model cannot be run locally there is no way to debug it. More test cases that would cover most common mistakes would be quite useful. Otherwise the only way through is to burry into forum topics for hours.

By Rosario C

Jan 05, 2018

The lectures were messier compared with the previous courses. Lot's of problems with the grading tools. The content of the course is great, so I would recommend it to others, modulo warning the others about being more patient :)

By G C

Mar 25, 2018

Covers interesting material and practical problems, and tries to get the student to implement useful tools, but there is a large disconnect between the understandable theory and frameworks used to implement the solutions.

By Victor P

Nov 29, 2017

Good course, but with the conjunction of the poor quality of the Coursera interface, video quality, the price does not feel like a great bargain. Still I feel confident I can be efficient after following this course.

By Sebastiano B

Oct 21, 2019

Exercises were purposly difficult because of obscure API documentation and quirks (not because the problem itself was difficult). Good school in debugging, I personally disagreed with it (V3 if I remember correctly).

By Rob W

May 14, 2018

Enjoyed the course but the programming assignments weren't well designed I think. They were more about debugging than applying what was learned. I preferred the assignments of the earlier courses of this curricilum

By Denys G

Dec 04, 2017

The production of the course felt rushed, there are numerous clipping issues in the videos and a major bug in one of the assignments. Also, for such a key topic to be covered in only 4 weeks felt very shallow.

By Emanuel S

Jan 22, 2018

Good explanations of the material but bugs in homework assignments and better explanations of tf usages is required for certain assignments. A refresher of tf via an additional assignment would've been nice.

By Daniel M d C

Jan 27, 2018

Good insights on the YOLO algorithm as well as in Siamese networks and triplet loss. Miss some more deeper understanding both in the lectures and the assignments, but I totally recommend the course anyway.

By Ashwin m

Jul 22, 2019

very good topics discussed ,facial recognition and facial verification assignments do not do justice to the complexity involved.practical knowledge gained is less compared to other modules prior to this.