A Sketchy Introduction to Convolutional Neural Nets

Source: Deep Learning on Medium

A Sketchy Introduction to Convolutional Neural Nets

I would like to try something new, at least something new for me:

Explore some of the core concepts of convolutional neural networks, but not by writing a huge amount of text and maybe some code snippets- there are plenty of excellent posts and papers about CNNs in exactly this format already.

Instead, I would like to try a different approach, asking questions about CNNs and then trying to answer them. Yes, with some text, but mostly visually.

So, without further ado, let’s get started!

And those were some of the key concepts of Convolutional Neural Nets.

We explored:

  • cnn use cases
  • filters/kernels
  • translation invariance
  • padding
  • pooling

So, what do you think, was this helpful gaining some intuition about those concepts?

I would love to hear your questions!

Who knows, I might do a follow-up, answering some of those visually.

Personally, I had a lot of fun trying out this different take on approaching CNNs by asking questions and sketching the answers.