Convolutional Neural Networks
About Course
Free Convolutional Neural Networks Course from Coursera
Learn about the evolution of computer vision and its applications such as autonomous driving, face recognition, and radiology image analysis. This course is part of the Deep Learning Specialization, which covers the capabilities, challenges, and consequences of deep learning.
By the end of this course, you will be able to:
* Build a convolutional neural network, including recent variations such as residual networks
* Apply convolutional networks to visual detection and recognition tasks
* Use neural style transfer to generate art
* Apply these algorithms to a variety of image, video, and other 2D or 3D data
This course is completely free and available on Theetay. We offer a wide range of free online courses from platforms like Udemy, Udacity, Coursera, MasterClass, NearPeer, and more.
Course Content
01_foundations-of-convolutional-neural-networks
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A Message from the Professor
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01_computer-vision.mp4
05:43 -
02_edge-detection-example.mp4
11:30 -
03_more-edge-detection.mp4
07:57 -
04_padding.mp4
09:49 -
05_strided-convolutions.mp4
09:01 -
07_convolutions-over-volume.mp4
10:44 -
08_one-layer-of-a-convolutional-network.mp4
16:10 -
09_simple-convolutional-network-example.mp4
08:31 -
11_pooling-layers.mp4
10:25 -
12_cnn-example.mp4
12:36 -
14_why-convolutions.mp4
09:40 -
15_yann-lecun-interview.mp4
27:48 -
Course Material Download Link
00:00
02_deep-convolutional-models-case-studies
03_object-detection
04_special-applications-face-recognition-neural-style-transfer
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