This project uses a Random Forest Regressor to predict the Gold Price (GLD) based on other financial indicators such as SPX (S&P 500), Oil Price, Silver Price, and USD Index. The model has been deployed as an interactive web app using Streamlit.
Gold price is influenced by various economic indicators. This project aims to build a machine learning model that can accurately predict the gold price by analyzing these features.
Tech Stack:
- Python
- Pandas, NumPy, Matplotlib, Seaborn
- Scikit-learn (Random Forest)
- Streamlit (for web deployment)
- Streamlit Cloud (for hosting)
🔗 Click here to view the deployed Streamlit App
(Replace the above link with your actual Streamlit Cloud app link)
- 📈 Visualizes correlation between gold price and financial indicators
- 🔍 Trains a Random Forest model on historical data
- 🧠 Makes predictions based on user input
- 🌐 Deploys the model with an interactive UI using Streamlit
- Clone the repository
git clone https://github.com/chandadiya2004/gold-price-prediction.git cd gold-price-prediction