4:11
Triangular Matrices and LU Decomposition - Explained
DataMListic
3:03
The Identity Matrix - Explained
4:28
Rotation and Reflection Matrices - Explained
8:08
Orthogonal Matrices - Explained
6:22
Symmetric Matrices and the Positive Definiteness
6:44
The Hessian Matrix - Explained
4:45
The Jacobian Matrix - Explained
8:11
Kernel Density Estimation - Explained
5:10
Accept-Reject Sampling - Explained
8:41
Dirichlet Distribution - Explained
9:17
Markov Chain Monte Carlo (MCMC) - Explained
5:27
Bayes' Theorem - Explained
1:17
sum of squared errors #maths #statistics #datascience #machinelearning
4:49
Taylor Series - Explained
