Jupyter notebooks with notes, code, and exercises from Linear Algebra: Theory, Intuition, Code by Mike X Cohen (2021).
Python code (Jupyter notebooks) used in the lecture "Mathematics of Machine Learning".
Linear Discriminant Tree in jupyter notebook
some notebooks of all technics of data analysis
The notebooks I worked on during the Numerical Computing course, covering topics such as SVD, nonlinear equations, LSQ, polynomial regression, unconstrained optimization and image enhancement.
PCA or truncated SVD reduces dimensionality of data by transforming the data into a lower-dimensional space. In this notebook a chart visualizes how much variance of the original data is picked up in the new components. The data transformation process is also explained.
Add a description, image, and links to the svd topic page so that developers can more easily learn about it.
To associate your repository with the svd topic, visit your repo's landing page and select "manage topics."