FINAL

Final Project: Mathematics Behind a Machine Learning Model

Objective

Students will select one machine learning model and explain the mathematics that makes it work.

Project Components

• Description of the problem
• Mathematical ideas involved
• Visual explanation (plots or diagrams)
• Python implementation
• Reflection on assumptions and limitations

Example Models

• Linear Regression
• Logistic Regression
• k-NN
• Naive Bayes
• PCA
• Simple Neural Network

Evaluation Criteria

Criterion	Weight
Mathematical Understanding	40%
Clarity of Explanation	25%
Python Implementation	20%
Reflection & Insight	15%