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Usage | |
1. Clone the Repository | |
Start by cloning the repository to your local machine: | |
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git clone https://github.com/your-username/your-repository-name.git | |
2. Install Dependencies | |
Navigate to the project folder and install the necessary dependencies using the requirements.txt: | |
bash | |
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cd your-repository-name | |
pip install -r requirements.txt | |
3. Setup API Key | |
You will need an Alpha Vantage API key to fetch stock data. Sign up for a free API key here. | |
Once you have the key, replace the placeholder in the TESTING.py script: | |
python | |
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ALPHA_VANTAGE_API_KEY = 'YOUR_API_KEY' | |
4. Run the Stock Prediction | |
Run the script with your desired stock ticker symbol. The stock ticker should be in the format of TICKER.SYMBOL (e.g., AAPL for Apple, MSFT for Microsoft): | |
bash | |
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python TESTING.py | |
You will be prompted to enter the stock ticker symbol in the terminal: | |
java | |
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Enter the stock ticker symbol (e.g., TATAMOTORS.NS or TSLA): MSFT | |
5. View Results | |
The model will: | |
Output performance evaluation metrics (MAE, MSE, RMSE, R² Score). | |
Display a plot comparing actual vs predicted stock prices. | |
Predict the next hour’s stock price based on the last available data. | |
Example Output: | |
yaml | |
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📏 MAE: 3.5777, MSE: 18.7211, RMSE: 4.3268, R² Score: 0.9984 | |
📈 Predicted next hour price: ₹425.67 | |
The prediction results will be displayed graphically and saved as prediction_plot.pdf. | |