


Geometric Spaces
This lecture overviews Geometric Spaces that has many applications in Machine Learning and Digital Signal Processing and Analysis. It covers the following topics in detail: Vector Spaces, Affine Spaces, Metric Spaces.



Linear Algebra
This lecture overviews Linear Algebra that has many applications in Machine Learning, Computer Vision and Scientific Computing.



Z Transform
This lecture overviews Z Transform that has many applications in signal processing and systems theory.



Signal Sampling
This lecture overviews Signal Sampling that has many applications in signal acquisition, processing and analysis.



Laplace Transform
This lecture presents Laplace Transform (LT) and its region of convergence. Its relation to Laplace transform is presented. Notable LT properties are reviewed: time shift, convolution, signal differentiation/integration.



State – Space Equations
This lecture overviews State –Space Equations that has many applications in digital filters, systems theory and deep learning.