Scientific Computing

Numerical methods: eigenvectors and SVD, then PCA, interpolation, Fourier, and the probability side (MLE and Bayesian update).

The interpolation videos below are in Turkish, since that is the lecture language for this course.

Drawings

Topic	Items
Matrix operations	Eigenvectors and eigenvalues, determinant for 3x3 matrix, Singular Value Decomposition (SVD)
Principal Component Analysis (PCA)	Variance, covariance
Interpolation I and II	Polynomial interpolation, 3-point and 4-point examples
Fourier	Fourier series, formulas, Fourier transform
MLE	Likelihood, Gaussian distribution, Poisson distribution, full process under the hood
Bayesian update	Old / updated mean, old / updated variance, measurement, measurement noise
Optimization	Optimization techniques

The links I actually used, pulled straight off the canvas. One row per video.