Machine Learning DesignPRO

Dimensionality Reduction: PCA, Manifold Learning, and Production Trade-offs

A practical, interview-focused guide to dimensionality reduction covering the curse of dimensionality, projection, manifold learning, PCA, SVD, explained variance, PCA variants, Kernel PCA, LLE, t-SNE, feature selection, evaluation, leakage, and ML system-design trade-offs.

Deepak Mishra·31 August 2026·20 min read