Phase 5 · Exploratory Data Analysis & Feature Engineering
TopicsDimensionality Reduction (PCA Overview)
Part of the Data Science Roadmap.
Summary
A preview of Principal Component Analysis — reducing many correlated features into fewer, uncorrelated components that capture most of the original variance, covered in depth in Phase 8.
How to Learn This
- 1Read a conceptual (non-mathematical) explanation of what PCA does.
- 2Identify a dataset with many correlated features where PCA might help.
- 3Revisit Phase 8 for the full mechanics once you reach unsupervised learning.
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