This is Collection of Regularization Deep learning techniques with code and paper

This work is part of mathematical research I carried out in 2019 leading to my MSc thesis at Ignatius Ajuru University. MATLAB was used for numerical simulation and Python was used for analysis and visualisation.

Course assignment for Algorithm and Massive Datasets comparing SAD and SSD for motion estimation. Includes analysis of accuracy, speed (Python/NumPy), and error sensitivity. Highlights trade-offs for speed-critical vs. precision-focused applications.

Simulate random walk and calculate ℓ1-distance between normalized degree vector and empirical frequency vector