Neural Networks
The basics of neural networks, and the math behind how they learn
But what is a Neural Network?An overview of what a neural network is, introduced in the context of recognizing hand-written digits.
Gradient descent, how neural networks learnAn overview of gradient descent in the context of neural networks. This is a method used widely throughout machine learning for optimizing how a computer performs on certain tasks.
Analyzing our neural network
What is backpropagation really doing?An overview of backpropagation, the algorithm behind how neural networks learn.
Backpropagation calculusThe math of backpropagation, the algorithm by which neural networks learn.
Large Language Models explained brieflyA lightweight intro to LLMs, laying the foundation for the following lessons.
Transformers, the tech behind LLMs | Deep Learning Chapter 5A visual introduction to transformers. This chapter focuses on the overall structure, and word embeddings
Attention in transformers, step-by-step | Deep Learning Chapter 6Demystifying attention, the key mechanism inside transformers and LLMs.
How might LLMs store facts | Deep Learning Chapter 7Unpacking the multilayer perceptrons in a transformer, and how they may store facts.