A collection of hands-on, multi-page workshops where I dig deep into topics by building and experimenting rather than just reading. These were mostly AI generated (although meticulously reviewed) using my /handson-workshop skill. The format is inspired by my experiences at AMLC (Applied Machine Learning Conference) workshops, an excellent format for actually internalizing ideas rather than passively absorbing them.
Workshops
Batch Norm vs Vanishing Gradients
A 6-module hands-on workshop exploring how batch normalization tames the vanishing gradients problem in deep networks. Covers the math step by step, from the sigmoid activation and loss functions all the way through to why batch norm works, what it actually computes, and a few classic pitfalls. Includes worked experiments with plots and visualizations. I put this together while working through Andrej Karpathy's neural networks series (the makemore videos) to really understand BN before moving forward in the course.
6 modules · includes diagrams and experiment plots · final exam included