XGBoost
XGBoost Derivation +
Recent posts
Getting Up to Speed with SHAP for Model Interpretability
Value proposition, intuition, and analytical breakdown of SHAP
Logistic Regression Deep Dive
Derivation of objective and gradient, visualizing a gradient update
Notes on PCA Theory
These are non-comprehensive notes on the theoretical machinery behind Principal Component Analysis (PCA)
Blog Post Series: From KL Divergence to Variational Autoencoder in PyTorch
Landing page for the blog post series