Python Quick Wins (PQW)

Welcome to the Python Quick Wins (PQW) GitHub repository! This repo is a companion to the Python Quick Wins blog series, dedicated to delivering straightforward and digestible tutorials on loading and utilizing a wide range of Python libraries, with a focus on machine learning and computer vision.

The purpose of the PQW blog series is to bridge the gap for beginners or those unfamiliar with specific libraries, by offering clear, concise introductions without overwhelming the reader with complex examples.

Repository Contents

In this repository, you will find:

1. Notebooks: Complete Jupyter notebooks for each blog post, containing step-by-step code examples and explanations.
2. Environment Files: YAML files for setting up suitable environments to run the provided notebooks, ensuring a hassle-free experience when using the provided code.
3. Supplementary Materials: Any additional files or resources needed for running the notebooks, such as sample datasets or images.

Getting Started

To get started with the Python Quick Wins notebooks, follow these simple steps:

1. Clone the repository:

   git clone https://github.com/edparcell/python-quick-wins.git
   

2. Navigate to the repository's root directory:

   cd python-quick-wins
   

3. Create a new conda environment using the provided environment.yml file:

   conda env create -f environment.yml
   

4. Activate the newly created environment:

   conda activate pqw
   

5. Launch Jupyter Notebook:

   jupyter notebook
   

6. Open the desired notebook and start exploring!

Contributing

If you'd like to contribute to the Python Quick Wins repo, please follow these guidelines:

1. Fork the repository.
2. Create a new branch with a descriptive name.
3. Make your changes or additions, ensuring they align with the overall goals of the project.
4. Submit a pull request with a clear description of your changes.

We appreciate your contributions and look forward to building a valuable resource together!

License

Please note that different parts of this repository are licensed under different licenses, depending on the libraries used in the corresponding notebooks. The intent is for each notebook to be released under a license that respects the licenses of the libraries it utilizes.

When using or distributing content from this repository, it is important to adhere to the specific licenses associated with the libraries used in each notebook. In general, the licenses for each library will be specified in the respective notebook or a LICENSE file in the same directory.

If you are a library author and feel that your library's license has not been respected in any of the content within this repository, please do not hesitate to reach out to me at ed@edparcell.com, and I will address your concerns promptly.

For any content not associated with a specific library, the default license for this repository is the MIT License. See the LICENSE file for more information.

Contact

If you have any questions or suggestions, please feel free to reach out by emailing me at ed@edparcell.com or by opening an issue on this repository. Happy coding!