Machine Learning (Mar 2019)
EE 5841 is a machine learning class taught by Dr. Tony Pinar at Michigan Tech. I enjoyed this class a lot because I got to use Python and Docker to solve real-world problem.
Project 1
In this project, I explored regression techniques with a focus on Ridge and Lasso shrinkage methods to enhance model performance and prevent overfitting. I implemented and compared these approaches using Python, applying them to real-world datasets to analyze their impact on feature selection and prediction accuracy.
Project 2
In this project, I explored linear classification methods, including logistic regression and support vector machines (SVMs), to solve classification problems.
Project 3
I worked with ensemble learning methods, including Random Forests and Gradient Boosting, to improve model accuracy and robustness. Using Python, I applied these techniques to challenging datasets and evaluated performance using metrics like accuracy.