Backpropagation in CNN is one of the very difficult concept to understand. And I have seen very few people actually producing content on this topic.

So here in this video, we will understand Backpropagation in CNN properly. This is part 1 of this tutorial, and in this is we will just look at Backpropagation for Convolutional Operation. In part 2, we will see how the gradients propagate backward in the entire architecture.

All the frameworks used for Deep Learning automatically implement Backpropagation for CNN. But as we humans are curious, we want to know how it works and not let it be implemented automatically.

So buckle up! And let's understand Backpropagation in CNN.



Timestamp:
0:00 Intro
1:49 What to obtain
4:22 dL/dK
11:46 dL/dB
13:20 dL/dX
18:51 End



PDF notes for this video: https://bit.ly/BackPropCNNP1



Follow my entire playlist on Convolutional Neural Network (CNN) :

CNN Playlist: https://www.youtube.com/watch?v=E5Z7FQp7AQQ&list=PLuhqtP7jdD8CD6rOWy20INGM44kULvrHu&t=0s

At the end of some videos, you will also find quizzes that can help you to understand the concept and retain your learning.



Complete Neural Network Playlist: https://www.youtube.com/watch?v=mlk0rddP3L4&list=PLuhqtP7jdD8CftMk831qdE8BlIteSaNzD&t=0s

Complete Logistic Regression Playlist: https://www.youtube.com/watch?v=U1omz0B9FTw&list=PLuhqtP7jdD8Chy7QIo5U0zzKP8-emLdny&t=0s

Complete Linear Regression Playlist: https://www.youtube.com/watch?v=nwD5U2WxTdk&list=PLuhqtP7jdD8AFocJuxC6_Zz0HepAWL9cF&t=0s



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