Machine Learning Fundamentals
Principal Component Analysis
A dimensionality reduction technique that transforms data into orthogonal components ordered by variance explained.
Related Concepts
- Dimensionality Reduction: Explore how Dimensionality Reduction relates to Principal Component Analysis
- Eigenvalues: Explore how Eigenvalues relates to Principal Component Analysis
- Linear Transformation: Explore how Linear Transformation relates to Principal Component Analysis
Why It Matters
Understanding Principal Component Analysis is crucial for anyone working with machine learning fundamentals. This concept helps build a foundation for more advanced topics in AI and machine learning.
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This term is part of the comprehensive AI/ML glossary. Explore related terms to deepen your understanding of this interconnected field.
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machine-learning-fundamentals dimensionality-reduction eigenvalues linear-transformation