Mathematics of Deep Learning

I’ve been wanting to do this over the past two years. My first publication in my PhD was in Deep Learning (DL). Link to my paper is at the bottom of the post. I even talked about it in my video series. I had to learn DL from scratch to apply it on my data (microscopic images of chromatin inside human cells). Since I love Mathematics, I made this series focusing on the Mathematics behind DL. Artificial Intelligence (AI) is a buzz word these days. However, it is important to understand the basics behind it. I will mainly discuss image classification using convolutional neural networks (CNN).

Here’s an overview of what I will be talking about:

1. How neural networks behave and the logic that’s used
2. Mathematical functions and operators behind CNN
3. How computers recognize images
4. My research using Deep Learning
5. How to get started and what to learn
6. Can machines understand? Philosophical arguments against AI

These videos were inspired by Luis Serrano and I have used his technique to explain how CNN works. Please check out his channel on Serrano Academy.

My research paper can be accessed here:

https://www.molbiolcell.org/doi/full/10.1091/mbc.E20-11-0689

Paper title: Performance of deep learning restoration methods for the extraction of particle dynamics in noisy microscopy image sequences

Author name: Fadil Iqbal