CIS 053 Intro to Machine Learning Final Project
Use Python, Scikit to perform feature selection, lasso and ridge regression, cross validation on housing price data
20+ hour Final project to culminate all content mastered over the summer term.
Programming Tasks: descriptive statistic and generate plots including correlation heatmap, perform manual analysis of plots for potential relevant features, perform feature selection with Recursive Feature Elimination, build regularized regression model (Lasso and Ridge methods), use K-fold method for cross validation
Produced Final Report concisely presenting data and findings.
Here is a link to the full code (Juypter Notebook): Link to full code