Chevron Left
Back to Convolutional Neural Networks

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

4.9
stars
42,318 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

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.

OA

Sep 3, 2020

Great course. Easy to understand and with very synthetized information on the most relevant topics, even though some videos repeat information due to wrong edition, everything is still understandable.

Filter by:

4701 - 4725 of 5,613 Reviews for Convolutional Neural Networks

By Derek T

•

Feb 1, 2018

The content is not as high quality as the previous courses. Im still fuzzy on some of the material. But this is still world class, please accept my gratitude for this unprecedentedly great content!

By Srinivas

•

Jun 1, 2019

Course is good. It will be really awesome if there is a sample example scenario of assignment with code to practice before going to the assignment directly, so that learners can learn very easily.

By Martin B

•

Mar 7, 2019

Great material! I felt the last week was not as interesting or strong as the other ones, but I think I came out with a good idea of what ConvNets are and how to apply them in TensorFlow and Keras.

By Nicola P

•

Nov 22, 2017

Amazing lectures as usual for Ng's courses. Nevertheless programming exercises are like "drawing connecting the dots": some additional effort would be useful in order to "deeply learn" the subject

By Rahul P

•

Sep 16, 2020

Most Amazing Course on CNN. Every Concept Is explain by Andrew Ng is crisp and clear. Programming assignments are well designed and very important for getting the point. highly recommended course

By Liangyu Z

•

Sep 22, 2019

This course has a little jump for using keras and tensorflow. There were parts where i had to look up a lot of tensorflow manuals to figure out. Hopefully there could be more information on that.

By Shringar K

•

Jul 28, 2019

Very nice and crisp explanations with hyperparameters , I wish he had explained the segmentation part and other image processing techniques in deep as well. Neverthless this is a 4.5 star deal !

By Brandon C

•

Dec 9, 2018

If you are not yet familiar with Tensorflow, the programming assignments are much more tedious than necessary. However, the explanations of the theory are quite helpful in visualizing convolution

By Matthew W

•

Jan 20, 2018

Some programming assignments do not have the same level of "finish" as the other deep learning / machine learning courses by the same instructor, but very good in-depth material that helps a lot.

By James B

•

Nov 22, 2017

Great material, but the programming assignments feel like more of an exercise in figuring what the author is thinking than a challenge for me to learn the tools necessary to go do this on my own.

By Jinit M J

•

Aug 8, 2019

The overall course was excellent. It's just that I wanted to learn some more real-life based applications of conventional neural network. Thanks a lot for this course. It was a great help for me

By Arjan H

•

Jan 12, 2018

This specialization needs to have a guided challenging final project. The projects are spoon fed and great for learning. However, a certification should require a more challenging final project.

By Luciano N C

•

Oct 4, 2020

This course is really great, the explanations are very clear and easy to follow. The lab environment uses a very outdated TensorFlow version, making it difficult to find official documentation.

By Ajitesh S

•

May 10, 2020

There were some topics which were taught in last chapters, however, had they been in beginning could have given better understanding. Like 1-D 3-D conv, intuition about deep hidden layers etc.

By Wentao S

•

Sep 16, 2018

Overall an excellent course, but some hints and guides of the assignments are not clear or misleading. If you work through them however, you will gain a lot (on how to implement these models).

By Johannes B

•

Feb 10, 2018

As machine vision engineer, I was most curious for this one. And I haven't been disappointed. "Secrets" of convolutional architectures are revealed in a way that they are no more rocket scienc

By thomas m

•

Dec 21, 2017

Would like to see more of an involved exercise for either keras or tensorflow, perhaps using tensorboard visualizations. Good introduction into CNNs and where the art/science currently stands.

By Sean K

•

Nov 27, 2017

Some bugs to work out of the course content and I think the team should post the slides. The hands-on technical training is very good. I'm looking forward to implementing these in my own work

By Shawn

•

Mar 31, 2020

Excellent course, hope it adds more instructions on tensorflow and keras. wasted a lot of times debugging programming exercise due to tensorflow functions and structures. but fun experience!

By PETER O

•

Dec 2, 2019

The Deep Learning courses taught by Prof. Andrew Ng and his team have laid a solid foundation for me to kick start an interesting career in AI. Thanks to Coursera for this great opportunity.

By Camilo M

•

Dec 17, 2017

Good course. Would have been great to see a little bit more of the history of how these filters or convolutional operators came about, and what is the mathematical motivation and properties.

By Yujie L

•

Jul 22, 2019

The course is great, but it's almost impossible to learn in China without a vpn. Even if I got a VPN, I cannot connect to the jupyter notebook stably. And the course project is quite easy..

By Diwakar R

•

Sep 4, 2018

The grader is not robust enough to find out if the code is correct. It fails for semantic differences (not errors) even when the correct output is obtained, the grader still grades is wrong

By Moustafa S

•

Jun 22, 2020

the projects was not so helpful, even tho i learned by the end of course 5 that this is just the technical stuff, and the coding projects is in other coursers of specializations, so thanks