Using UCI boston dataset created a model and looking for promising attributes, finding out correlations, plotting graphs, creating a pipeline, dealing with missing values and saving the model using joblib.

HousePricePrediction ML Model

Machine learning model that predicts house prices based on multiple factors. This model was trained on the following data from Kaggle: "House Prices - Advanced Regression Techniques".

No description available

This project predicts California housing prices using ML models (Linear Regression, Random Forest, XGBoost, CatBoost, LightGBM). It includes a training script (HousePricePrediction.py) for model building/evaluation and a Streamlit app (app.py) for interactive predictions, with saved models and visualizations.