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Avis et commentaires pour d'étudiants pour Convolutional Neural Networks par deeplearning.ai

4.9
étoiles
37,039 évaluations
4,817 avis

À propos du cours

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....

Meilleurs avis

AG
12 janv. 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.

RS
11 déc. 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.

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226 - 250 sur 4,768 Avis pour Convolutional Neural Networks

par Irina M

2 avr. 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.

par Tun C

15 août 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.

par D M

13 juin 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.

par Felix H K

6 sept. 2020

As EXCELLENT as other courses in deep learning specialization.

Must do progamming assignment by yourself to get hands-on experience and deeper understanding of what you learned from lectures.

I would like to express my sincere appreciation to Prof. Ng and all staffs who prepared this excellent course and programming assignments.

par Felippe T A

21 mai 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 DeepLearning.ai.

par Wei W

10 janv. 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.

par keerthi k

21 févr. 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.

par Abhishek K S

4 févr. 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.

par ANSHUMAN S

4 juin 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

par Nick H

22 mai 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

par Keetha N V

20 oct. 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!

par Wang F

14 janv. 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。

par Edson C

3 sept. 2020

This was the most difficult course I did in this specialization, but I loved it, I loved it very much. Thank you very much dr. Andrew and coursera for the opportunity, I really understand the importance of studying computer vision and this course was very useful in this journey. Thank you very much, I really loved ...

par 杨建文

10 janv. 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.

par Krishna M G

23 juin 2020

This Course was exceptional and upto mark. I learnt a lot of stuff easily and was able to implement into the real world example. This was really helpful for building up my resume. I thank Andrew Ng and Coursera team for giving financial aid to take up this course. The amount of knowledge gained is so valuable to me.

par Eric C

23 juin 2019

Awesome. This course was much more dense than the other ones, there is so many areas to review. Since this course is about my favorite subject, I will need to pause and rework on each individual points and associated papers (yolo, nst, similarity learning) which will probably take me weeks... Prof Andrew is the best

par Arvind N

2 nov. 2017

I thoroughly enjoyed taking this course. Beautifully designed...Thank you!

I had written a detailed review of the first 3 deeplearing.ai courses at : https://medium.com/towards-data-science/thoughts-after-taking-the-deeplearning-ai-courses-8568f132153

I will review this CNN course as well, in the form of a blog post.

par Benjamín V A

9 juil. 2020

Great course, provided many clear explanations I has been searching before. The one thing they could improve is that some of the practical exercises seem more focused in the framework than the algorithms. (I spent more time googling how to pass parameters to specific functions than actually using the algorithms)

par Wade J

25 mars 2018

Good amount of challenge for after work learning. Nice exposure to different applications of AI. Fun.

Andrew Ng is awesome at explaining the concepts. Almost anybody would be able to understand them after he presents them. I also appreciate how genuine he is. You can trust that there is merit to what he tells you.

par Glenn P

10 déc. 2017

Another excellent course. Convolutional Neural Networks is no longer a mystery. I like the fact that Andrew doesn't teach this as an academic class but has a very practical approach that can be applied right way. He lets you know the strengths and weakness of each of the NN and gives his personal opinion as well.

par Yijie

15 mai 2018

It is a great course that covers most part of Convolutional Neural Networks. I have learned a lot from it. Thanks Andrew! Only one suggestion: we have learned dropout and the batch norm in previous courses. Because they are such important tricks, it would be better if you could cover how they can be used in CNN.

par Ahmad B E

4 nov. 2017

Greatest cores for me till now on deep learning. I recommend it for deep learner or computer vision student. The best thing in this course is that it is very practical and up to date, and full of research papers of algorithms that Google and Facebook currently uses. Thanks a lot Prof Andrew Ng you are the best.

par Parab N S

25 août 2019

An Excellent Course to make people understand Convolutional Neural Networks in good depth and with ease. The detailed understanding of the major Convolutional models like YOLO and ResNet is like an icing on the cake. I would like to thank Professor Andrew N.G. and his team for developing this wonderful course.

par Alejandro M v G

5 août 2019

Muy bueno para empezar a entender los conceptos de las capas convolucionales. Luego muestra modelos profundos como AlexNet, VGG16, ResNET, Inception que se pueden entrenar usando transfer learning. La parte de detección de objetos es la mas complicada. La parte que más me gusto fue la de reconocimiento facial.

par Jeffrey T

30 mars 2020

The intuition and examples made this course easy to understand and learn. I loved how Andrew decomposed current published papers into an easy to understand format. All of the important points to remember were highlighted without wasting time on the minutia. Thanks for all the hard work put into the course.