https://www.saitejabandaru.com/learn Tutorials, derivations and research notes on statistics, machine learning, NLP and clinical data science by Sai Teja Bandaru. en-us © Sai Teja Bandaru. Licensed under CC BY-NC 4.0. Saitejaroyal2311@gmail.com (Sai Teja Bandaru) Saitejaroyal2311@gmail.com (Sai Teja Bandaru) Fri, 12 Jun 2026 00:00:00 GMT Fri, 12 Jun 2026 00:00:00 GMT 1440 https://www.saitejabandaru.com/uploads/professional-favicon.png https://www.saitejabandaru.com/learn https://www.saitejabandaru.com/learn/kernel-density-estimation https://www.saitejabandaru.com/learn/kernel-density-estimation Sai Teja Bandaru Statistics Probability Machine Learning Mon, 02 Jun 2026 00:00:00 GMT A non-parametric way to estimate the shape of any distribution — kernels, bandwidth selection (Silverman, cross-validation), and practical Python. https://www.saitejabandaru.com/learn/binary-cross-entropy https://www.saitejabandaru.com/learn/binary-cross-entropy Sai Teja Bandaru Machine Learning Information Theory Evaluation Mon, 19 May 2026 00:00:00 GMT The loss function behind every logistic regression and binary classifier — derivation, numerical stability, class imbalance, and calibration. https://www.saitejabandaru.com/learn/kl-divergence https://www.saitejabandaru.com/learn/kl-divergence Sai Teja Bandaru Information Theory Probability Machine Learning Mon, 05 May 2026 00:00:00 GMT What KL divergence measures, why it's asymmetric, when to use forward vs. reverse KL, and how it shows up in cross-entropy and variational inference.