ILearnDeepLearning.py

Why we included this project

Most deep learning tutorials hand you a finished model and ask you to trust it; this one opens the hood. Each project builds a neural network in plain NumPy, so you can actually trace how gradient descent moves weights and what activation functions do before seeing the same ideas reappear in Keras. The visualizations carry a lot of the teaching, with classification boundaries drawn frame by frame as training runs and gradient descent plots that make the math easier to follow. There is real computer vision material here too, including a YOLO object detection walkthrough, so you get beyond toy examples. Every topic pairs with a Medium article the author wrote, which makes it a good self-paced study path for anyone who wants to read, run, and modify the code.