This project demonstrates the application of Polynomial Regression to analyze and predict manufacturing performance metrics. It provides a practical implementation of this regression technique using Python libraries, visualizations, and real-world manufacturing data.
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Polynomial regression modeling for non-linear data.
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Data preprocessing and exploratory analysis.
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Model evaluation metrics for performance comparison.
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Visualization of regression curves and predictions.
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Python 3.x
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Libraries: numpy, pandas, matplotlib, sklearn
- Clone the repository:
git clone <repository-url>
- Install required dependencies:
pip install -r requirements.txt
- Open the Jupyter Notebook:
jupyter notebook Polynomial_Regression_Manufacturing.ipynb
- Follow the step-by-step implementation within the notebook.
This project is licensed under the MIT License. See the LICENSE file for details.