Data Preparation for Machine Learning: Categorical and Numerical Data

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Explores the analysis of velocity data in biomechanics using Excel for visualization and interpretation.

Covers unsupervised learning, focusing on dimensionality reduction and clustering, explaining how it helps find patterns in data without labels.

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Covers the Spark runtime architecture, including RDDs, transformations, actions, and caching for performance optimization.