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Convolutional Neural Networks(으)로 돌아가기

Convolutional Neural Networks,

(21,122개의 평가)

About this Course

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....

최상위 리뷰

대학: 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.

대학: FH

Jan 12, 2019

Amazing! Feels like AI is getting tamed in my hands. Course lectures , assignments are excellent. To those who are not well versed with python - numpy and tensorflow , it would be better to brush up.

필터링 기준:

2,565개의 리뷰

대학: WangMeiqin

May 21, 2019

Great! Continue to learn!

대학: dbw413

May 21, 2019

Some exercises may not clearly explain its aim and they might be better if we could engage more into the implementations.

Anyway, it is a course that worth to learn.

대학: 翁瑶

May 21, 2019

It's difficult,but I have learned more.Thanks.

대학: 杨庆

May 20, 2019

very good course assignment and learning curve.

대학: Einar Wigum Arbo

May 20, 2019

An error with the "Face recognition" notebook, otherwise a great and in-depth course

대학: 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.

대학: Ayon Banerjee

May 19, 2019

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


May 19, 2019

Very nicely explaimed

대학: 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.

대학: jamescxchen

May 18, 2019