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Opiniones y comentarios de aprendices correspondientes a Convolutional Neural Networks por parte de

34,655 calificaciones
4,436 revisiones

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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....

Principales revisiones


Dec 12, 2019

Great Course Overall\n\nOne 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.


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

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201 - 225 de 4,397 revisiones para Convolutional Neural Networks

por balaji

Dec 25, 2017

As a beginner I have learnt a lot of topics with good clarity. Assignments have given me good understanding of the topics learnt.

I think the assignments should some more difficult and students should be able to spend some more time understanding the code and writing code of their own.

Thank you very much for making learning affordable and easy.

por William v

Dec 07, 2017

The libraries needed such as tensorflow, might need to better support (a special segment on them beyond the overview). Those models are complex and deep and using those libraries wasn't clear to me even though I managed to get the solutions, I needed time to study those libraries and they are rich and complex. I enjoyed the course immensely.

por Wanda L

Feb 16, 2020

Fantastic course about Convolutional Neural Networks! For me the best part of the course (and the specialization, too) is the assignment. You could hardly find a similar friendly, supported and easy-to-follow homework elsewhere in the world, even in some universities. Thanks to Andrew, and thanks to all teaching assistants in the community!

por Eddy P

May 27, 2019

All are pretty good! Except for the low speed while running the training process which I think have in fact hurt the course's completeness. Because we have skipped many important training processes and instead use pretrained models to save time. I suggest maybe we can collaborate with Google and put the programming assignments on the Colab.

por Tu L

Nov 07, 2017

Another amazing course from Prof Andrew and his colleagues. I've had a very exciting time to get to know about various CNN architectures, as well as to be able to implement, even just small part of them, and to make them work in practice. Thanks team a lot and look forward to seeing other courses from you in the near future.

por Harshavardhan S

Nov 05, 2017

Awesome Course...You have gone out of your way to make the programming exercise simple enough for beginners to get a taste of very recent algorithms. thank you for your effort. I really loved the course. And it has given me enough to get me interested in and capable of following Computer Vision literature on my own with greater confidence.

por Prakash M

Feb 14, 2020

Wonderfully designed course for beginners to know all about CNNs. Even experienced professionals can have all their concepts cleared not only in CNNs, but also in YOLO and it's applications in object detection. Thank you very much Coursera Team for all your efforts in making this course accessible to thousands of aspiring data scientists.

por Paul M

Apr 23, 2020

Your courses are really great. I love the simplicity of the explanations followed by very advanced notebooks. Thnak you very much for your work. I appreciate a lot ! Maybe one observation. Personnaly I find the notebooks too guided and easy. Maybe you could write less in the notebooks and more links like you do with Hints. Thanks again

por Yedhu K V P

Jun 29, 2018

This course helped me to learn in detail about convolutional neural networks. I have heard of CNN, but this is the first time I am trying it out myself. It's interesting and fun to learn. I'm planning to do more projects using the ideas learned from this course. I highly recommend this course to any aspiring machine learning student.

por Muhammad M K

Feb 23, 2018

An amazing course! Not only does the course covers seminal work in the area of deep learning related to image processing but it shares valuable insights into problem solving and provides hands on experience. If there is a single course that I have to recommend to anyone related to deep learning for image processing, this would be it.

por Rajthilak M

Apr 23, 2018

The lectures were excellent and helped me understand the key elements of convolutional neural networks. I enjoyed coding the assignments and building foundation knowledge for building real-world AI applications. Thanks to the very strong foundation ,I am able to read and interpret many of the real world AI experts' blog and views.

por Deleted A

Nov 27, 2017

This is really a superb course. Andrew Ng has the ability to clearly explicate the complexities of convolutional networks. The coverage of topics such as residual networks, face recognition, Yolo, and neural style transfer are both intriguing and informative. I found the programming assignments challenging, but deeply instructive.

por Minsheng L

Apr 11, 2020

a really nice class. I learned different techiques like CNN, YOLO, and used them to do face recognition, style transfering.... This calss is comprehensive. I need repeating many time before I can really master all of them. Thanks for the instructors, and all the people who have contributed to this calss. I've really learned a lot.

por Irina M

Apr 02, 2019

Thank you for the course and I really like it. Learn a lot and I made few teaching sessions of DeepLearning algorithm for Women Who Code, where I am mentor in leadership group. I clarified many things for myself during the course, I very grateful for the amazing knowledge and experience! I will recommend this course to colleagues.

por Tun C

Aug 15, 2018

I appreciate the way professor Ng made the Convolutional Neural Networks concepts and architectures easy to understand. This course gave a very good overview and professor Ng presented the intuition behind the concepts as usual. The programming assignments are also a good mix of under-the-hood and high-level application of CNN.

por Gabriel A M P

Jun 13, 2020

A good course, i feel like it only grasps the surface of the subject, but very good, feels way too easy should remove the rails because it feels way too streamlined and gives you very little room to wiggle, but the video content was very good and gives you the tools to understand the papers and the investigation on the subjects.

por Felippe T A

May 21, 2020

A great course!! The content was very deep and it was presented to us some important CNN. For me, for this course be better, it needs a final project, but I can understand due to the large amount of content. But, in general it is a great course, maybe the best available on the internet. Thanks Coursera, thanks

por Wei W

Jan 10, 2018

This is a great intro to deep learning/AI course. Professor Ng has a way to explain things in a way that is super easy to understand. Basic knowledge (college level, but no need to be math/cs major) on linear algebra is required. If you are in science/engineer major, and took any kind of linear algebra class, you will be OK.

por keerthi k

Feb 21, 2020

Thank you so much Coursera. I have been doing this specialization properly, but suddenly I had an accident which took almost 10 days to become normal. During those time several assignments were overdue, but Coursera extended their assignments deadline twice and helped me complete this course. So once again I thank Coursera.

por Abhishek K S

Feb 04, 2019

The CNN is always found as one of the trickier concepts to follow and it was actually very hard for me to figure out what these Conv layers are doing. But this course is so robust and easy to follow that I was even able to read the research papers on advanced CNN architectures with relative ease. Thanks to Andrew and team.


Jun 04, 2019

It has been a great journey through learning CNNs it was quite interesting rather than all other courses and I got to know really very new ideas which i can implement in my own models.

Once again I want to thanks Andrew Ng and all other teachers of Course

and a special thanks to Coursera for giving me this ample opportunity

por Nick H

May 22, 2019

Awesome course if you want to understand the basics of CNNs along with recent applications of these algorithmns.

As usual, both Andrew's material and his presentation style kept me both engaged and interested to a point that I got ahead of the weekly schedule...which is probably a good metric in terms of course success

por Keetha N V

Oct 20, 2019

Great course by Andrew Ng sir. It gives us a great insight into many case of studies of state of the art ConvNet. Gives us a lot of intuition about object detection systems in autonomous driving and landmark detection , one shot learning for face recognition and a fun way of applying ConvNets for neural style transfer!

por Wang F

Jan 14, 2018

Despite the confusing bug and server running problem in the last assignment of happy house ,

the course is still great . Compare to the other three ones, it's the hardest course for me by now .

You may feel stuck in some practice questions and program .Worth spending time to review the

stuffs of the course again。

por 杨建文

Jan 10, 2018

The last 2 courses were delayed, but the positive side for me is that, in the beginning I proceed too fast and didn't learn that well, the delay made me take more time on such a valuable course, carefully reading and memorizing the instructions of assignments. I'm really grateful for Prof. Ng's excellent instructions.