The Periodic Table of Machine Learning: Beyond Supervised vs. Unsupervised

goyalshaliniuk · x · 2026-09-01

This post breaks down machine learning into a structured ecosystem of strategies and algorithms, moving beyond the simple supervised vs. unsupervised dichotomy. It details four major learning types and their key components:

• Supervised Learning: Learning from labeled data (Loss Functions, Overfitting, Cross-Validation).
• Unsupervised Learning: Discovering hidden patterns (Clustering, Dimensionality Reduction, Anomaly Detection).
• Reinforcement Learning: Interacting with environments for rewards (Agent & Policy, Exploration vs. Exploitation, MDP).
• Semi-Supervised Learning: Using mixed labeled and unlabeled data (Co-Training, Pseudo-Labeling).

Mastering these foundations strengthens your capabilities as a data scientist or AI practitioner.

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