Data Science and Machine Learning (Theory and Projects) A to Z - Feature Extraction: Dimensionality Reduction Pipelines

The video tutorial covers various feature extraction and dimensionality reduction techniques, focusing on methods like PCA, kernel PCA, ISOMAP, and LLE. It explains how to implement these techniques using scikit-learn, including data preparation and importing necessary packages. The tutorial also highlights the importance of building pipelines for efficient data processing and discusses the challenges of using neighborhood-based methods due to their computational intensity.

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