Polish bird species recognition - Bird song analysis and classification. Women in Machine Learning & Data Science project.
Analysis and modelling of Polish birds songs
├── LICENSE├── Makefile <- Makefile with commands like `make data` or `make train`├── README.md <- The top-level README for developers using this project.├── data│ ├── external <- Data from third party sources.│ ├── interim <- Intermediate data that has been transformed.│ ├── processed <- The final, canonical data sets for modeling.│ └── raw <- The original, immutable data dump.│├── docs <- A default Sphinx project; see sphinx-doc.org for details│├── models <- Trained and serialized models, model predictions, or model summaries│├── notebooks <- Jupyter notebooks. Naming convention is a number (for ordering),│ the creator's initials, and a short `-` delimited description, e.g.│ `1.0-jqp-initial-data-exploration`.│├── references <- Data dictionaries, manuals, and all other explanatory materials.│├── reports <- Generated analysis as HTML, PDF, LaTeX, etc.│ └── figures <- Generated graphics and figures to be used in reporting│├── requirements.txt <- The requirements file for reproducing the analysis environment, e.g.│ generated with `pip freeze > requirements.txt`│├── setup.py <- makes project pip installable (pip install -e .) so src can be imported├── src <- Source code for use in this project.│ ├── __init__.py <- Makes src a Python module│ ││ ├── data <- Scripts to download or generate data│ │ └── make_dataset.py│ ││ ├── features <- Scripts to turn raw data into features for modeling│ │ └── build_features.py│ ││ ├── models <- Scripts to train models and then use trained models to make│ │ │ predictions│ │ ├── predict_model.py│ │ └── train_model.py│ ││ └── visualization <- Scripts to create exploratory and results oriented visualizations│ └── visualize.py│└── tox.ini <- tox file with settings for running tox; see tox.testrun.org
Project based on the cookiecutter data science project template. #cookiecutterdatascience