Github link to download the codes: https://github.com/prashant9501/YT_Videos_Resources/tree/main/Linear%20Algebra
Master the core concepts of Eigenvalues, Eigenvectors, and Principal Component Analysis (PCA) in this beginner-friendly Linear Algebra for Data Science tutorial. Learn step-by-step how to compute Eigenvalues and Eigenvectors mathematically, understand dimensionality reduction using PCA, and explore real-world applications in machine learning and data science. 🚀
Topics Covered:
✅ Eigenvalues & Eigenvectors
✅ Principal Component Analysis (PCA)
✅ Characteristic Polynomial
✅ Solving for Eigenvalues
✅ Finding Eigenvectors
✅ PCA for Dimensionality Reduction
Whether you're a data scientist, AI researcher, or student, this video will build your foundation in linear algebra for machine learning. Don’t forget to like, comment, and subscribe for more AI and data science content!
