From Basic Backprop to Adam & Regularization.
Move from "it works on my machine" to "it works in production." In this session, we transcend the basic Multi-Layer Perceptron by implementing industry-standard optimization and stability techniques. We will dive deep into the Adam Optimizer to understand adaptive momentum and bias correction, and master L2 Regularization to solve the universal challenge of overfitting. By the end of this workshop, you will have the mathematical foundation and the Python implementation needed to transform a simple classifier into a robust, generalizable Deep Learning model.