Data Party THU

Jul 24, 2026 · Fundamentals

Maximum Likelihood Estimation Explained Simply: Core Principles, Code Walkthroughs, and Limitations

This article demystifies maximum likelihood estimation by using a coin‑flip example to contrast probability and likelihood, introduces log‑likelihood for numerical stability, shows Python implementations for discrete and continuous cases, discusses historical origins, and highlights practical limitations such as small‑sample bias and over‑fitting.