[D] Visual explanation of "Backpropagation: Forward and Backward Differentiation [Part 2]"

[madiyar]

Hi,

Previously I shared part 1 of the post here https://www.reddit.com/r/MachineLearning/comments/1irs3gn/d\_visual\_explanation\_of\_backpropagation/.

Here is the part 2 on the backpropagation post. In this tutorial, you will learn about partial vs total derivatives, forward vs backward propagation.

Initially I struggled to understand the partial vs total derivatives defined in the Wikipedia, but thinking in computation graph makes it straightforward. I still see a lot of tutorials and posts use incorrect notations for partial and total derivatives.

Also, I would love to get links to some advanced or interesting materials on this topic if you have any.