This project uses Support Vector Regression (SVR) to predict stock prices based on the day of the month. It downloads historical stock price data from Yahoo Finance and performs regression analysis.
Before running the code, make sure you have the following libraries installed:
- yfinance
- pandas
- numpy
- scikit-learn
- matplotlib
You can install these libraries using pip:
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Clone the repository to your local machine:
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Navigate to the project directory:
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Run the Jupyter Notebook or Python script to execute the SVR model for stock price prediction.
The project uses historical stock price data for the specified stock and date range. You can modify the stock symbol and date range in the code.
The code includes the evaluation of the SVR model using R-squared (R2) and root mean squared error (RMSE). It assesses the model performance on both the training and testing datasets.
This project is open-source and available under the MIT License.
Have a great time on GitHub!