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Avis et commentaires pour l'étudiant pour Convolutional Neural Networks par

24,947 notes
3,007 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


Jan 13, 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.


Sep 02, 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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76 - 100 sur 2,968 Examens pour Convolutional Neural Networks

par Anurag A

Jan 01, 2019

Nuts and bolts of Convolution Neural Networks - this is the course. The assignments are great source of in-depth understanding

par Shish P

Jan 02, 2019

Well organized and Conceptual course.

par Arun T S

Jan 01, 2019

Best one I've ever seen

par Amit P

Dec 31, 2018

Very happy with the course - CNN was a concept I had heard a lot about and this course provided everything I needed to know to understand it in detail and implement it. Thanks Andrew for making this course.

par Anubhav B

Jan 01, 2019

This is one of the best courses on CNNs which is simple yet deeply insightful :)

par Rohit N

Jan 02, 2019

Awesome course! Thank you a lot.

par Matheus A F

Jan 26, 2019

Another excellent course for those who are beginners or have some intuition behind neural networks and need to hone skills, like me.

par Jayaram R

Jan 28, 2019

Andrew's explanations, and the exercises are absolutely fantastic. There seems to be a lot of tricky math in Convolution Neural Networks and Andrew's explanations and illustrations help students understand the essential concepts behind each type of Conv net.

par 白思开

Jan 28, 2019


par Antonio H M

Jan 27, 2019

Excelllent Course. Great theater. Excellent material.

par Nyamerdene O

Jan 28, 2019

It is a very excellent course. It including from CNN's foundation to the latest Deep CNN architecture.

par Martin Z

Jan 27, 2019

Thanks a lot for this great course :-) Learned a hell lot!

par Ruiliang L

Jan 26, 2019

Excellent course. Lay the foundation for computer vision and nlp

par Pavel K

Jan 27, 2019

This course provides a great introduction to CNNs. Further, it nicely explains recent killer-apps!

par Daniel J D

Jan 04, 2019

Andrew Ng's courses and Geoffrey Hinton's are about as good as courses get--rigorous, practical, and yet fairly thorough in the underlying theory. Convolution Neural Networks is certainly no exception to that as he goes into res nets and inception nets.

par Andrei V

Jan 03, 2019

Very robust introduction to Convolutional Neural Networks. The lessons are, as always, very concise and the programming exercises help consolidate anything that might have not been easily grasped.


Jan 04, 2019

Great Learning. Thanks


Jan 30, 2019

Excellent course content!

par Yuqing Z

Jan 29, 2019

Very nice ConvNet Intro course.

par Jorge C

Jan 30, 2019

Very grateful for this awesome course.

par Borja

Jan 29, 2019

Great course!

par Anand R

Jan 30, 2019

Good Course. Thank You for Provide financial aid for this

par Asher L

Jan 30, 2019

Very good.

par Cesar L A C

Feb 01, 2019

A brilliant course! ... Yolo algorithm was very stimulating.

par Ricardo A

Jan 31, 2019

Great real-life and cutting edge applications of CNNs!