Linear Algebra for Data Science: Practical Applications with Python

Overview

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This course applies singular value decomposition and principal component analysis with Python to data manipulation, feature engineering, and dimensionality reduction. Learners use these techniques in practical data science projects and domain-specific problems.

Syllabus

Use linear algebra techniques like singular value decomposition (SVD) and principal component analysis (PCA), for advanced data manipulation, feature engineering, and dimensionality reduction in data science projects using Python.
Apply Pythonic linear algebra to develop practical applications or solve real-world problems in their domains