Machine Learing and Data Mining Projects

Brief description: Implementation of machine learning models in Numpy in the context of UBC CPSC340.

Table of Contents

• About the Project
• Technologies Used
• Credit

About the Project

A1:

• Linear Algebra, Probability, and Calculus Review.

A2:

• Implement KNN, K-Means, Random Forest Classification.

A3:

• Implemented Least Square Sum, Weighted Least Square Sum.
• Linear Regression with Gradient Descent, Robust Regression with Gradient Descent.
• Least_squares with bias and polynomial_fits.

A4:

• L0, L1, L2 regularization.

A5:

• Stochastic Gradient Descent.

A6:

• Robust PCA.

Technologies Used

• List the programming languages, libraries, frameworks, and tools used in the project:
  • Python
  • Numpy

Credit

• Course Link
• UBC