Gold Price Prediction

Machine learning
Random Forest Regressor
Python
Scikit-learn
Matplotlib
Seaborn
Pandas

The Gold Price Prediction Model utilizes a Random Forest regressor to forecast gold prices based on diverse parameters such as stock market indices (SPX), silver prices (SLV), oil prices (USO), and currency exchange rates (EUR/USD). This model employs a Random Forest, a powerful ensemble learning technique, which combines multiple decision trees to predict gold prices. By training on historical data that includes variations in stock market indices, silver and oil prices, and currency exchange rates alongside gold price movements, the Random Forest model comprehends complex relationships among these factors.

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Feature Description
  • SPX: Stock Market Indices
  • USO: The oil (petrol) price
  • SLV: The price of silver
  • EUR/USD: The ratio between euro and US dollar

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Most Used Packages
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Scikit-learn
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Pandas
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Numpy
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Seaborn
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