Soybean Futures Price Predictor
A machine learning pipeline and interactive app that forecasts soybean futures prices from historical market data.
- Role
- Machine learning engineering
- Technologies
- Python
- Pandas
- Scikit-learn
- XGBoost
- Streamlit
Overview
An end-to-end machine learning pipeline that forecasts soybean futures prices using historical time-series data from Yahoo Finance.
I engineered lag and moving-average features, trained XGBoost and Random Forest models, and compared their performance using RMSE.
An interactive Streamlit app lets you experiment with the models in real time and configure hyperparameters.
Highlights
- End-to-end pipeline from data ingestion to prediction
- Lag and moving-average feature engineering
- XGBoost and Random Forest models evaluated with RMSE
- Streamlit app for live experimentation and hyperparameter tuning