https://github.com/jpcadena/linear-regression-course
Linear Regression Course.
https://github.com/jpcadena/linear-regression-course
Last synced: about 1 month ago
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Linear Regression Course.
- Host: GitHub
- URL: https://github.com/jpcadena/linear-regression-course
- Owner: jpcadena
- Created: 2023-01-17T20:04:27.000Z (almost 3 years ago)
- Default Branch: master
- Last Pushed: 2023-01-17T20:23:53.000Z (almost 3 years ago)
- Last Synced: 2025-01-15T18:47:16.284Z (12 months ago)
- Language: Python
- Size: 59.6 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# linear-regression-course
Table of Contents
## About the project
[![Project][project-screenshot]](https://example.com)
This project is about Linear Regression...
### Built with
* [![Python][Python.org]][Python-url]
## Getting started
* [Python 3.10+][Python-url]
### Installation
1. Clone the **repository**
```
git clone https://github.com/jpcadena/linear-regression-course.git
```
2. Change the directory to **root project**
```
cd linear-regression-course
```
3. Create a **virtual environment** *venv*
```
python3 -m venv venv
```
4. Activate **environment** in Windows
```
.\venv\Scripts\activate
```
5. Or with Unix/Mac OS X
```
source venv/bin/activate
```
6. Install requirements with PIP
```
pip install -r requirements.txt
```
### Usage
1. If found **sample.env**, rename it with to **.env**.
2. Replace your **credentials** into the *.env* file.
3. Execute with console
```
python main.py
```
## Contributing
If you have a suggestion that would make this better, please fork the repo and
create a pull request.
1. Fork the Project
2. Create your Feature Branch (`git checkout -b feature/AmazingFeature`)
3. Commit your Changes (`git commit -m 'Add some AmazingFeature'`)
4. Push to the Branch (`git push origin feature/AmazingFeature`)
5. Open a Pull Request
Use docstrings with **reStructuredText** format by adding triple double quotes
**"""** after function definition.\
Add a brief function description, also for the parameters including the return
value and its corresponding data type.\
Please use **linting** to check your code quality
following [PEP 8](https://peps.python.org/pep-0008/).\
Check documentation
for [Visual Studio Code](https://code.visualstudio.com/docs/python/linting#_run-linting)
or [Jetbrains Pycharm](https://github.com/leinardi/pylint-pycharm/blob/master/README.md).\
Recommended plugin for
autocompletion: [Tabnine](https://www.tabnine.com/install)
## License
Distributed under the MIT License.
## Contact
LinkedIn: [Juan Pablo Cadena Aguilar][linkedin-url]
E-mail: [Juan Pablo Cadena Aguilar](mailto:jpcadena@espol.edu.ec?subject=[GitHub]linear-regression-course)
[linkedin-url]: https://linkedin.com/in/juanpablocadenaaguilar
[project-screenshot]: assets/images/project.png
[Python.org]: https://img.shields.io/badge/python-3670A0?style=for-the-badge&logo=python&logoColor=ffdd54
[Python-url]: https://www.python.org/
