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#pca

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MohitmSep 1

What PCA is actually doing to your data

It only sees variance, it never sees your target

7 min readmonthlydatascience.hashnode.dev

Divyajot KaurAug 6

Part 17: Principal Component Analysis (PCA): Simplifying Complex Data

Understand dimensionality reduction, variance, and principal components with simple real-life examples.

6 min readai-beginners-journey.hashnode.dev

Yejun ParkMay 30

From Thousands of Features to a Few: A Deep Dive into Dimensionality Reduction

Dimensionality reduction: why it matters, key challenges (curse of dimensionality, redundancy), and techniques to compress high-dimensional data.

13 min readyejunpark3.hashnode.dev

Anik ChandMay 24

#13 PCA

PCA (Principal Component Analysis) is a dimensionality reduction technique and helps us to reduce the number of features in a dataset while keeping the most important information. It changes complex d

8 min readanikchandml.hashnode.dev

Ayomide ZaccheausFeb 23

When the Machine Finds Patterns You Didn't Tell It to Look For

This is Week 19 of my data science journey, the week I stopped telling the algorithm what to find and started letting it discover patterns on its own. If you've been following since Week 18, welcome b

13 min readpapizee.hashnode.dev

UplatzDec 11, 2025

Dimensionality Reduction Techniques

Managing High-Dimensional Data for Better Performance, Interpretability, and Generalization

3 min readuplatz.hashnode.dev

Masir JafriNov 9, 2025

Feature Engineering - The Art of Shaping Data

Learn the art of Feature Engineering in Machine Learning - from handling missing data and scaling features to building powerful, model-ready datasets.

5 min readblog.masirjafri.in