stochasticgradientdescent

🧠 Hands-on AI & ML guide: from tensors to neural networks, with code, formulas, and model evaluation.

This project explores Boosting algorithms in Machine Learning, specifically focusing on AdaBoost for classification and Gradient Boosting for regression. It demonstrates how to handle imbalanced medical data using the ROC AUC metric and how to optimize regression models through stochastic sampling and hyperparameter tuning.