Grant Sanderson’s brilliant visual introduction to the mathematics of deep learning. Using intuitive animations, the series breaks down what a neural network actually is, how gradient descent works, and the core calculus behind backpropagation.

Andrej Karpathy’s masterclass series on building neural networks from scratch in Python. Starting from basic backpropagation up to building a full GPT-style transformer, this playlist is widely considered one of the most accessible and thorough resources for understanding deep learning from first principles.