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Convolutional Neural Networks, deeplearning.ai

4.9
20,240 notes
2,510 avis

À propos de ce 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

par 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.

par 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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2,473 avis

par Huijun Park

Apr 18, 2019

Great lectures but the programming assignments feel as if it is testing your proficiency with tensorflow which is neither formally covered in the lecture nor the most intuitive framework to understand so you'll spend so much time digging through convoluted tensorflow documents and qna and whatnot to debug your codes that you would rather learn tensorflow formally first and then take this course and still end up finishing it faster than only going through this course only but it is only the programming assignments that basically assume that you are already familiar with the tensorflow framework so if you are only going to go over the video lectures it gives a great overview of how CNN works and many useful algorithms which can applied to a assortment of situations

par eren atmaca

Apr 16, 2019

pretty helpful for the begineers

par Yan

Apr 15, 2019

I was always curious about the "CNN" concept every time it emerged in the news. Thanks to Prof. Andrew's mild explanation, now I get a straight intuition into it!

The assignments were very amusing in this section. It was not hard to get a pass with the help of forums, but understanding every step is more important I think. So I will come back to practice more.

par Saumya Tiwari

Apr 15, 2019

Good Explanation.

par Sebastian Javier Marchano

Apr 15, 2019

excellent

par Akash Singh

Apr 14, 2019

had a lot of fun in this course, i would, recommend every student to take up this course as it gave me an insight on how human eyes process images. this also helped me a lot to understand deep learning better

par Nikunjkumar Raval

Apr 14, 2019

Amazing course and content

par 郑笙桦

Apr 14, 2019

Means a lot.

par Pathairush Seeda

Apr 13, 2019

So impressive in both fundamental knowledge and the applications in computer vision.

par Pradeep Indrajith

Apr 13, 2019

Not easy, but gives you lot of confidence on the latest developments in deep learning.