https://github.com/batthulavinay/basic-linear-regression
This project demonstrates Basic Linear Regression using Python. The notebook includes dataset loading, exploratory data analysis, model training, evaluation, and visualization of results.
https://github.com/batthulavinay/basic-linear-regression
data-visualization datapreprocessing exploratory-data-analysis linear-regression matplotlib modelevaluation pandas-library
Last synced: about 2 months ago
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This project demonstrates Basic Linear Regression using Python. The notebook includes dataset loading, exploratory data analysis, model training, evaluation, and visualization of results.
- Host: GitHub
- URL: https://github.com/batthulavinay/basic-linear-regression
- Owner: BatthulaVinay
- Created: 2025-02-04T15:36:51.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-02-12T09:23:12.000Z (4 months ago)
- Last Synced: 2025-02-12T10:34:09.185Z (4 months ago)
- Topics: data-visualization, datapreprocessing, exploratory-data-analysis, linear-regression, matplotlib, modelevaluation, pandas-library
- Language: Jupyter Notebook
- Homepage:
- Size: 118 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Basic Linear Regression
## 📌 Overview
This repository contains a Jupyter Notebook demonstrating a basic implementation of linear regression. It covers data preprocessing, model training, and evaluation using Python and popular data science libraries.
## 🏗 Features
- Exploratory Data Analysis (EDA)
- Data preprocessing
- Implementation of Linear Regression using Scikit-learn
- Model evaluation using metrics like MSE and R-squared
- Visualization of regression results
## 📂 Files
- **Basic Linear Regression.ipynb**: Jupyter Notebook containing the complete implementation.
## 🛠 Requirements
Ensure you have the following libraries installed before running the notebook:
```bash
pip install numpy pandas matplotlib seaborn scikit-learn
```
## 🚀 Usage
1. Clone this repository:
```bash
git clone https://github.com/your-username/repository-name.git
```
2. Navigate to the directory:
```bash
cd repository-name
```
3. Open the Jupyter Notebook:
```bash
jupyter notebook "Basic Linear Regression.ipynb"
```
4. Run the notebook cell by cell to see the results.
## 📊 Results
- Scatter plot of data points
- Regression line visualization
- Model performance metrics
## 📜 License
This project is open-source and available under the MIT License.
## 🤝 Contributing
Contributions are welcome! Feel free to fork the repository and submit a pull request.