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PCA 102: Should you use PCA? How many components to use? How to interpret them?
Jan. 4, 2022, 10:53 p.m. | Tiago Toledo Jr.
Towards Data Science - Medium towardsdatascience.com
A dive on some more intermediate concepts on the PCA analysis
Photo by John Schnobrich on UnsplashThe Principal Component Analysis (PCA) is one of the most used dimensionality reduction techniques in the realm of Data Science. Because of its importance, improving our understanding of it is essential to better use the technique.
However, it is common to see on introductory courses how the PCA is made and what it represents, however, there are some aspects that usually are not …
data processing data science dimensionality-reduction machine learning
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