Bayes' Theorem: Updating Probability with "New Evidence", the Core of AI and Statistics
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5 pages
Machine Learning
Method of Least Squares: Finding the 'Best Fit Line' for Scattered Data using Linear Algebra
Singular Value Decomposition (SVD): Decomposing Any Matrix into Rotations and Scaling for Data Compression and AI
Eigenvalues and Eigenvectors: Special Vectors That Don't Change Direction Under Matrix Transformations and Their Applications
Gram-Schmidt Process: An Algorithm to Realign Distorted Basis Vectors into Neat, Mutually Orthogonal Vectors
