european-soccer from arthur960304 – Github Help

Data Analysis and Machine Learning with Kaggle European Soccer Database

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Dataset

Kaggle European Soccer

Built With

  • Python 3.6.10

  • numpy >= 1.16.2

  • matplotlib >= 3.1.1

  • PyTorch >= 1.7.0

  • scikit-learn >= 0.23.1

  • pandas >= 1.0.5

Code Organization

.
├── src                         # Python scripts
│   ├── prediction              # Prediction scripts
│   │   ├── utils.py            # Utility set for prediction
│   │   ├── sklearn_test.py     # Script for testing sklearn model
│   │   ├── models.py           # Define PyTorch objects
│   │   └── soccernet.py        # Neural network training and prediction
│   ├── visualization           # Visualization scripts
│   │   ├── pca_kmeans.py       # Perform PCA and Kmeans to the data
│   │   ├── visual_utils.py     # Utility set for visualization
│   └── └── visual.py           # Data visualization script
├── european_soccer.ipynb       # Notebook showing all results
└── README.md

How to Run

There are two ways you can do to get the results.

  1. Directly run the jupyter notebook (recommended)
  2. Run the scripts (See section About the scripts to get more info)

About the scripts

There are four files you can run

Results

Please refer to the notebook to see the result.

Read more here: Source link