The Random Number Predictor is a Python project that utilizes machine learning to predict the next number in a sequence generated by a random process. This project is designed to showcase the implementation of a simple online learning approach, where the model is continuously updated with new datasets, retaining and improving its knowledge over time.
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Linear Regression Model: The project employs a basic linear regression model for simplicity. This model is updated with both historical and new datasets to make predictions about the next number in the sequence.
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Online Learning: The script supports online learning, allowing the model to accumulate knowledge from past datasets and incorporate new information each time the code is run.
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Random Number Generation: Actual and predicted next numbers are displayed, providing insights into the model's performance.
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Clone the Repository:
git clone https://github.com/yourusername/random-number-predictor.git cd random-number-predictor -
Run the Script:
python randomPredictor.py -
Explore and Experiment:
- Observe actual and predicted next numbers before and after each update.
- Experiment with different datasets and explore the model's adaptability over time.
Contributions are welcome! Whether you want to improve the existing model, explore different machine learning algorithms, or add new features, feel free to fork the repository and submit a pull request.
This project is licensed under the MIT License.
This project was inspired by the curiosity to explore the dynamics of machine learning in predicting seemingly random sequences. Special thanks to the open-source community for providing valuable resources and tools.
Happy predicting!