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

4.9
stars
42,319 ratings

About the Course

In the fourth course of the Deep Learning Specialization, you will understand how computer vision has evolved and become familiar with its exciting applications such as autonomous driving, face recognition, reading radiology images, and more. By the end, you will be able to build a convolutional neural network, including recent variations such as residual networks; apply convolutional networks to visual detection and recognition tasks; and use neural style transfer to generate art and apply these algorithms to a variety of image, video, and other 2D or 3D data. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI....

Top reviews

AV

Jul 11, 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

RS

Dec 11, 2019

Great Course Overall

One thing is that some videos are not edited properly so Andrew repeats the same thing, again and again, other than that great and simple explanation of such complicated tasks.

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5326 - 5350 of 5,613 Reviews for Convolutional Neural Networks

By Chris M

•

Aug 2, 2019

The assignments are less copy paste and some allow the student to explorer different NN architectures. However, most of the videos are still a waste of time. And the methods needed to complete the assignments aren't taught to the student. Instead you have to spend a lot of time searching and hoping you find the right method.

By André N

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Dec 2, 2018

video courses were really good, but the programming assignments drove me nuts. I am a senior software developer and I am writing software for more than 10 years now. I had a really hard time understanding the Tensorflow code. I think it is better to suggest a student to learn the basics of Tensorflow before doing this course

By Tuấn T L

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Dec 22, 2021

This course is well organized with CNN knowledge. However, it seems like the team is overwhelmed to maintain both a big Tensoflow tech stack in programming assignments while keeping academic science core concepts. Some code comments are outdated and the mentors definitely can not follow up all the issues raised by students.

By Mladen M

•

Jan 20, 2020

Couple of suggestions: 1) fix the artwork via neural networks assignment as there is a bug in your code 2) With the lectures I would suggest that you do a summary explanation of how the whole process works (all steps and motivation - a review) at the end of each group of lectures (one for artwork one for face recognition)

By Cristian G

•

Oct 13, 2022

I think this course lacks hands-on experience, and for that I think it should improve the labs, people would learn much more from a youtube-kind tutorial than from these "#your code starts here / #your code ends here"-labs.

The quiz interface is horrible, i need to refresh my browser many times before it loads properly.

By Do Q B

•

Jun 11, 2018

The theory is very good but the exercise part is not good enough for me (For example in the Face Recognition exercise, I'd like to build (even a simple model) and train the triplet loss function... However, all that I can do is only loaded a trained model and then apply some simple similarity measure on encoding vector)

By Ernesto G d l P

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Apr 11, 2021

There is major room for improvement on the automatic grader, under some particular cases, the answers are correct but the grader will give you zero with no feedback (in my case, I made a mistake with declaring local variables as global in the code). This issue is quite frustrating, the forums helped a lot though.

By Anthony M

•

Dec 4, 2017

Great class and amazing assignments. I really enjoyed learning about CNNs, YOLO, and Neural Style Transfer.

Errors with submitting the assignments, particularly weeks 2 & 4 took away considerably from the overall satisfaction with the course.

Thank you once again for providing a rich learning environment. :)

By Christopher C

•

Sep 9, 2020

Programming assignments were not to the level of the prior courses in the series. Should have more illustration of using Keras/Tensorflow. Assignments either were too spoon fed or there was too little reference information whereas prior courses had a good balance. Many of the keras links are dead.

By Luis F A

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Jun 9, 2019

Theoretical content was very informative and high quality. However, some problems with the programming assigments were annoying. For instance, for the last programming assigment some weights would not load and it was necessary to go get the weights from the github repository of some other person.

By Shreyash W

•

Jan 6, 2020

The week 1 and 2 were perfect, then week3,4 had some issues with the lectures- Andrew sir was repeating some parts and the problems/corrections in the slides.Also the week3 object detection was tough n the hints were not enough, with the errors in the assignment submission costing me a day

By Achille H

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Jul 6, 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 Cory N

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Feb 2, 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

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Feb 7, 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

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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 Jaspreet S

•

Mar 9, 2022

The course gives a high level understanding of CNN's, which is good but missing details. The content is okay. However, Andrew sounds very monotone and I happend to lose me focus very quickly in that case. Also, the many errors and corrections are confusing sometimes.

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 H

•

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 Esmaeil K G

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Dec 1, 2020

Thank you for your great course, but, to me, it has a great problem. It proposed the general theory of ConvNet and then explained some applications on ConvNet. there was nothing in between, i think it could be better if ConvNets were explained more deeply.

By Linying M

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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

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Jul 14, 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 Max S

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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

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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

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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.