This article discusses the importance and implementation of dimensionality reduction techniques, specifically t-SNE and PCA, in Python. It provides detailed explanations and practical guidance, making it a valuable resource for data scientists and enthusiasts.

An overview of t-SNE and PCA techniques

Dimensionality Reduction in Python

DataCamp. High-dimensional datasets can be overwhelming. Learn how feature extraction techniques can reduce dimensionality for you through the calculation of uncorrelated principal components...

Dimensionality Reduction in Python - Towards Data Science

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