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Simple-Linear-Regression

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# Simple-Linear-Regression

This notebook implements a simple linear regression model using Python's popular data analysis and machine learning libraries, such as `pandas`, `numpy`, and `matplotlib`. It demonstrates the basic principles of linear regression, where the goal is to fit a linear equation to a set of data points in order to predict future values.

### Key Features:
- **Data Preprocessing**: It starts by importing and cleaning the data to ensure it’s ready for model training.
- **Model Training**: The notebook demonstrates how to apply the simple linear regression model to a dataset.
- **Visualization**: It includes data visualization using `matplotlib`, providing clear insights into the relationship between the dependent and independent variables.
- **Prediction**: Once the model is trained, it makes predictions on new data based on the fitted linear model.
- **Evaluation**: The performance of the model is evaluated using key metrics, such as the coefficient of determination (R²).

### Dataset: on kaggle:
https://www.kaggle.com/datasets/ezzaldeenesmail/fuel-consumption-co2/data

This notebook is ideal for those looking to understand and apply basic machine learning techniques in Python, especially for regression tasks.

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Simple-Linear-Regression

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