
Machine Learning Series Chapter 1
MICROGRAD FOR MORTALS TL;DR Let’s use Micrograd to explain core ML concepts like supervised learning, regression, classification, loss functions, and gradient descent. We’ll break down how models adjust weights and biases during training using backpropagation. Through simple code examples, it visualizing how gradients flow through a minimalistic neural network. Intro This article deviates from the […]