/dimensionality-reduction

Exploration challenge with PCA and how we can get smaller data sets through it, using the FIFA 2019 dataset.

Primary LanguageJupyter NotebookMIT LicenseMIT

Dimensionality Reduction

Exploration challenge with PCA and how we can get smaller data sets through it, using the FIFA 2019 dataset which originally contains 89 variables with different attributes of more than 18 thousand FIFA 2019 game players.

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Prerequisites   |    Getting started   |    How to contribute   |    License

☑️ Prerequisites

🆙 Getting started

  • Clone this repo
  • Enter the folder dimensionality-reduction
  • Run pip install -r requirements.txt to install the dependencies
  • Run jupyter notebook to start the local jupyter environment
  • Access http://localhost:8888/

✏️ How to contribute

  • Make a fork;
  • Create a branck with your feature: git checkout -b my-feature;
  • Commit changes: git commit -m 'feat: My new feature';
  • Make a push to your branch: git push origin my-feature.

After merging your receipt request to done, you can delete a branch from yours.

📝 License

This project is under the MIT license. See the LICENSE for more information.

Made with by Roberto Sousa 👋 Get in touch!