Classical ML and Deep Learning
A Mathematical Deep Dive Into the Curse of Dimensionality
Mathematically understanding the surprising phenomena that arise when dealing with data in high dimensions.
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Classical ML and Deep Learning
Why Bagging is So Ridiculously Effective At Variance Reduction?
Diving into the mathematical motivation for using bagging.
Engineering Best Practices
Sklearn Models are Not Deployment Friendly! Supercharge Them With Tensor Computations.
Speed up sklearn model inference up to 50x with GPU support.
Classical ML and Deep Learning
Gaussian Mixture Models (GMMs)
Gaussian Mixture Models: A more robust alternative to KMeans.
Classical ML and Deep Learning
HDBSCAN: The Supercharged Version of DBSCAN (An Algorithmic Deep Dive)
A beginner-friendly introduction to HDBSCAN clustering and how it is superior to DBSCAN clustering.
Classical ML and Deep Learning
DBSCAN++: The Faster and Scalable Alternative to DBSCAN Clustering
Addressing major limitations of the most popular density-based clustering algorithm — DBSCAN.
Classical ML and Deep Learning
Formulating and Implementing the t-SNE Algorithm From Scratch
The most extensive visual guide to never forget how t-SNE works.
Classical ML and Deep Learning
Bayesian Optimization for Hyperparameter Tuning
The caveats of grid search and random search and how Bayesian optimization addresses them.
