Some exercices from my Data Science courses where I apply two methods for Single Value Decomposition for Principal Component Analysis. The first method is a standard SVD which requires high CPU consumption when working on large datasets. Then, for that reason, I applied a Truncated Single Value Decomposition which outputs similar values with a more efficient computation time.