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Convolutional Neural Networks,

(оценок: 21,157)

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....

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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: 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.

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Рецензии: 2,571

автор: Aravindaraja Puthiyavinayagam

May 22, 2019

Excellent way of presentation, which even helps beginners to catch hold of the concepts.

автор: Nick Hall

May 22, 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

автор: Naveenkumar SM

May 22, 2019

Best place to start learning about CNN

автор: Rafael Cauduro Dias de Paiva

May 21, 2019

The content is really great. It is giving very good overview on the state of the art, and how convolutional neural networks can be useful. I think it is hard to get such a great overview in current deep learning books that usually focus on more theoretical aspects, which are covered in this course. The only negative point I would say is that is it not always easy to understand how to use some very specific python tools, and one can easily get stuck into implementing a single line of code. However, the discussion forum provides great resources to solve these issues.

автор: Animesh Sinha

May 21, 2019

Great course, concisely conveys both techniques and advice for practical implementation of Neural Networks in Image recognition. Great for a person who is already familiar with the idea of Deep Learning and want to take it forward, and ties in perfectly with the specialisation.

автор: Mashrur Mahmud

May 21, 2019

Really gives you a lot of things to think about and work on. Excellent course.

автор: WangMeiqin

May 21, 2019

Great! Continue to learn!

автор: 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.

автор: 翁瑶

May 21, 2019

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

автор: 杨庆

May 20, 2019

very good course assignment and learning curve.