Housing Prices Prediction using Machine Learning Developed a regression model to predict housing prices using data preprocessing, feature engineering, and various regression algorithms. Tuned hyperparameters and evaluated performance with key metrics (RMSE, MAE, R²).

This project involves training a machine learning model and plotting its learning curves to analyze training and testing accuracies, utilizing Java for model execution and Python for data visualization. It includes commands for compiling and running the Java program, generating plots, and sending results via email.

This project aims to build a model which classifies the type of an unseen image as accurate as possible, by implementing, evaluating, and comparing amongst 2 different multi-layer perceptron Neural Networks.

Implementation of step generation algorithm for learning curve analysis on code-writing data from our EDM 2024 paper.