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

4.9
étoiles
37,050 évaluations
4,818 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

AR
11 juil. 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
1 sept. 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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201 - 225 sur 4,769 Avis pour Convolutional Neural Networks

par Pin Z

24 juin 2018

This is a very good course to get to know the basic concepts of CNN and to start hands-on programming to implement CNN. Andrew's lecture gives very clear explanation of the principles of CNN, as well as introduction to state-of-the-art example network structures. The exercises help to build essential skills to program CNN using TensorFlow and Keras.

par Youssef H

10 avr. 2018

I have really learned a lot from taking this course. During the course you will be exposed to the state of art deep learning architectures by understanding the theory behind them in lectures and then you will get to implement them in the assignments. I have taken the first three courses and I think that definitely this course is by far the best one.

par Elidor V

3 août 2020

The course was simply great. It starts from the real basics of Convolutions, gives you all the needed theoretical background, then starts to focus on real-life scenarios. Also worth mentioning that is not a piece of cake. The given assignments are not easy in general, but after completing those the benefit will be more than clear. 100% recommended!

par Nazmus S E

12 juin 2020

Although this course was a bit difficult compared to the previous one, it was more informative and taught a lot of real-life applications of CNN and Deep Learning. The assignments of Week3 and 4 involved pre-trained models. Explanations of them were not given but links to where we could learn about these models were given. Overall a great course.

par kumud C

17 mars 2020

I was scared of CNN and thought that it's quite overwhelming to learn such new concepts like Residual Network, YOLO, Face recognition. This course helped me in understanding these algorithms intuitively and practically. I loved watching videos and will watch in the future as well to revise the concepts I learned. Thanks to Coursera and Andrew Ng.

par Hector L

1 févr. 2020

I enjoyed this course. I learned a lot about Convolutional Networks and the assignments were very fun to complete. The assignments are difficult enough to lay the groundwork for the subject - but you definitely need to take your time to understand and probably run experiments on your own.

I loved the ResNet, YOLO, and Face Recognition assignments.

par Yogesh C

3 juin 2019

This course was amazing and interesting. The tutorials and quizzes were great. But I was looking for the implementation of CNN from scratch without using tensorflow.

Rest as mentioned this was an amazing course. Now, I have a better understanding of YOLO algorithm, face recognition, Neural style transfer. Thanks to Andrew and the rest of the team!

par Sadam H

20 déc. 2019

Learned some interesting concepts about different state-of-art ConvNets. Although I was hoping that in Face Recognition Programming exercise there would be some code implementation exercise or example about one-shot learning and Siamese network, it would have been perfect. Nonetheless, very nice structured course to learn intuitions intuitively.

par Abanoub A

22 sept. 2018

The Way Prof. Andrew explains things, taking us from simple stuff to the complex conclusions by ourselves making it so much easier and convincing!

The course content was great and assignments were fun, I like that in the end of each assignment there is always a cell that's like a "playing ground" allowing you try and test the models you created.

par Hardik V U

19 août 2018

This course is good from both the perspective: Research and Development. This course involves many real life applications which will help us to understand the real life problems and also will help in tacking such problems. So, I would strongly suggest to go for this course which builds the fundamental for computer vision and pattern recognition.

par Jatin s

4 oct. 2020

This was by far the most engaging and fun course in the entire specialisation.I guess as the concepts build up the tasks get more interesting and exciting.Their was a ton of content in this course , you need a very sound and solid background of the previous courses in this specialisation to get a firm hold of the concepts taught in this course.

par Okta F S

7 juil. 2020

This is very good course. From here you can learn so many things, start by learn basic convolutional operation, intro to some of ConvNet architecture like Inception, Residual block etc. And the most important thing is you can applied your knowledge to build some use case systems like object detection, neural style transfer, and face recognition

par balaji

24 déc. 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.

par William v

7 déc. 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.

par Wanda L

15 févr. 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!

par Eddy P

26 mai 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.

par Tu L

7 nov. 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 deeplearning.ai team a lot and look forward to seeing other courses from you in the near future.

par Harshavardhan S

4 nov. 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.

par Prakash M

14 févr. 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.

par Paul M

23 avr. 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

par Yedhu K V P

29 juin 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.

par Muhammad M K

23 févr. 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.

par Rajthilak M

23 avr. 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.

par Deleted A

27 nov. 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.

par Minsheng L

11 avr. 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.