

Decision Trees and Ensemble Methods
From single decision trees to random forests and gradient boosting - how combining models reduces error and when to use each approach.
Hypothesis Testing, Confidence Intervals and Power
The statistical decision-making toolkit - hypothesis tests, p-values, confidence intervals, power, and sample size planning.
Linear Regression
The simplest predictive model - how it works, how to fit it, what can go wrong, and how to fix it.
Model Evaluation
Loss functions, metrics, cross-validation, and diagnostic curves - how to measure whether your model actually works.
Regularization and Feature Selection
Preventing overfitting and choosing the right features - bias-variance trade-off, Ridge, Lasso, and feature selection methods.
Probability Basics
The rules of uncertainty: axioms, conditional probability, independence, and Bayes’ theorem.
Probability Distributions
The shapes data takes - random variables, PMF, PDF, CDF, and the key distributions you need to know.
The Central Limit Theorem
Why the normal distribution dominates statistics - sampling distributions, the law of large numbers, and the CLT.
Population, Samples and Descriptive Statistics
The starting point for statistics: what we measure, how we summarise it, and why the sample formula divides by n-1.
Building This Blog: Hugo + PaperMod + Cloudflare Pages
I wanted a blog that’s fast, cheap to host, and easy to maintain. After evaluating a few options, I landed on Hugo with the PaperMod theme, deployed to Cloudflare Pages. Here’s the full breakdown. The stack Static site generator: Hugo — fast builds, great templating, large ecosystem Theme: PaperMod — clean, minimalist, fast, well-maintained Hosting: Cloudflare Pages — free tier, global CDN, automatic deploys from GitHub Comments: Giscus — powered by GitHub Discussions Domain: Cloudflare Registrar (at-cost pricing, ~$10/year) Why Hugo? I considered Next.js, Astro, and Jekyll before settling on Hugo: ...