Topic

Artificial Neural Networks

A collection of 5 issues

Policy Gradients: REINFORCE from Scratch

Deep dive into Policy Gradient methods, specifically REINFORCE deriving the mathematical foundations as well as the implementation from scratch.

Advanced Feature Attribution Techniques for Deep Learning Models

Explainable AI: Exploring various techniques built to shed light on predictions made by deep learning neural networks.

Introduction to Graph Neural Networks: The Message Passing Framework

Exploring the fundamentals of Graph Neural Networks (GNNs), their applications and the underlying mathematical principles.

Artificial Neural Network Backpropagation

Diving deep into how backpropagation of (deep) neural networks work, from derivatives and the chain rule to gradient descent and delta updatess

The Transformer Architecture

Diving deep into the Transformer architecture and its mathematical underpinnings, covering scaled dot-product attention, multi-head attention, and positional encodings, ... . Exploring how encoder-decoder, encoder-only, and decoder-only models work for NLP, translation and generative AI.