Dimensionality Reduction in Machine Learning: Techniques, Applications, and Python Example

[Great Learning Editorial Team]

Learn how dimensionality reduction in machine learning simplifies high-dimensional datasets. Explore key techniques such as PCA, t-SNE, and UMAP, understand their applications, and implement PCA in Python using scikit-learn.