GLOSSARY TERM
What is Dimensionality Reduction?
The transformation of data from a high-dimensional space into a lower-dimensional one.
Dimensionality reduction retains meaningful properties of the original data while stripping away redundant variables. Techniques like PCA or t-SNE are critical for data visualization, noise reduction, and improving computational efficiency.
Streamline Data Analytics
Accelerate operational insights by compressing and distilling data features.