# Machine learning methods and validation

> Compare trees, clustering, PCA and validation without confusing training performance with evidence of generalization.

Prerequisites: Classification and basic probability.

Short self-study course; not an accredited qualification or a complete university syllabus.

## Lessons

- [Decision trees, splits and ensembles](https://studybrix.com/en/courses/machine-learning-methods/ai-trees/index.md): university; 8 questions.
- [Clustering, distances and interpretation](https://studybrix.com/en/courses/machine-learning-methods/ai-clustering/index.md): university; 8 questions.
- [PCA, variance and dimensionality reduction](https://studybrix.com/en/courses/machine-learning-methods/ai-pca/index.md): university; 8 questions.
- [Cross-validation, grouped data and time-aware splits](https://studybrix.com/en/courses/machine-learning-methods/ai-validation/index.md): university; 8 questions.