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Convolutional Neural Networks,

Оценки: 21,074
Рецензии: 2,592

Об этом курсе

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....

Лучшие рецензии

автор: AG

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.

автор: EB

Nov 03, 2017

Wonderful course. Covers a wide array of immediately appealing subjects: from object detection to face recognition to neural style transfer, intuitively motivate relevant models like YOLO and ResNet.

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Рецензии: 2,560

автор: Yao Feng

May 20, 2019

The course is pretty good with advanced techniques on computer vision. The only regret is one problem about the last coding homework. I failed to load the pre-trained model and can only finish the home work without checking the accuracy of designed examples.

автор: Ayon Banerjee

May 19, 2019

Concepts explained in great depth as compared to those found in most books.


May 19, 2019

Very nicely explaimed

автор: Zebin Chen

May 18, 2019

This course gives me a more intuitive understanding of the principles of CNN. I have mastered and implemented many classic CNN structures through the four-week course.

автор: jamescxchen

May 18, 2019


автор: Yisake Tadsse

May 18, 2019

The best place to learn CNNs

автор: XINQI

May 18, 2019

Please do not use too strict rules to check the assignment, I.e. IOU Func, it's a waste of time to debug.

автор: Stephen Van Kooten

May 17, 2019

The course does an very good job of explaining the concepts behind different types of neural networks, but the homework assignments pretty much only test these concepts. Students should not expect to gain any significant experience coding neural networks in keras/tensorflow.

автор: Agustinus Agri Ardyan

May 17, 2019

Prof. Andrew Ng, along with the team, successfully deliver advanced level course that is thorough, yet easy to understand.

автор: Abe Kang

May 16, 2019

Another winner. Prof Andrew Ng does it again.