PCA
Type: Concept
As of November 2026, PCA has been mentioned in one podcast episode on Kaggle (Aug 2025). Used to reduce dimensionality in the feature selection and engineering process.
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.
| Mentioned in | 1 episode on 1 podcast (as of November 2026) |
|---|---|
| First heard | Aug 2025 on Kaggle |
| Field | Machine Learning |
Who talks about PCA on podcasts?
PCA came up; the most recent mention was Aug 2025 on Kaggle.