5 docs tagged with "machine-learning"

Understand what Artificial Intelligence is, why it matters, and how it differs from traditional rule-based programming — the starting point for the AI-900 exam.

Understand what Machine Learning is, why it matters, and the key distinction between supervised and unsupervised learning — the conceptual foundation for AI-900 exam domain 2.

Understand the containment hierarchy AI ⊃ ML ⊃ DL with definitions, trade-offs, and a practical decision framework.

Master the essential ML vocabulary tested in AI-900 — features, labels, overfitting, underfitting, model evaluation metrics, and the train/validation/test split.

Understand the end-to-end Machine Learning lifecycle — from data collection to deployment — and the iterative nature of real-world ML projects.