Gold Price Prediction Using ML

Project Overview

The Gold Price Prediction project utilizes machine learning to analyze and predict gold prices based on historical data. The dataset includes financial and economic indicators such as the S&P 500 Index (SPX), United States Oil Fund (USO), Silver Prices (SLV), and the EUR/USD exchange rate. By applying advanced data analysis and machine learning models, this project aims to accurately forecast the gold price, aiding investors and analysts in making informed decisions.

Purpose and Applications

Gold prices are influenced by multiple economic factors. Accurately predicting these prices has significant implications for:

• Investment Strategies: Guiding investors in portfolio management.
• Economic Analysis: Offering insights into macroeconomic trends.
• Risk Mitigation: Helping financial institutions manage risks associated with gold price volatility.

Installation

To run the project locally, follow these steps:

1. Clone the repository:

   git clone https://github.com/BhaveshBhakta/Gold-Price-Prediction-Using-ML.git

2. Install required libraries:

   pip install pandas numpy matplotlib seaborn scikit-learn pandas-profiling

3. Place the gld_price_data.csv file in the project directory.
4. Execute the Jupyter Notebook or Python script for data preparation, visualization, and model training.

Collaboration

Contributions are welcome! Feel free to fork the repository, make improvements, and submit a pull request.