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ccv1: Deep Learning - Was versteckt sich da?

Patrick Schürmann, Luca Mazzotta & Marvin von Rappard

This project contains our submission for the ccv1 course at University of Applied Sciences in Brugg. The goal of this project is to classify images from camera traps in the Taï National Park. The results will be submitted to the DrivenData Competition.

Project Organization

├── LICENSE
├── Makefile           <- Makefile with commands like `make data` or `make train`
├── README.md          <- The top-level README for developers using this project.
├── data
│   ├── processed      <- The final, canonical data sets for modeling.
│   └── raw            <- The original, immutable data dump.
│
├── models             <- Trained and serialized models, model predictions, or model summaries
│
├── notebooks          <- Jupyter notebooks. The code controlling the experiments.
│
├── reports            <- Generated analysis as PDF & LaTeX
│   └── images         <- Pictures, figures and graphics that are used in the reports
│
├── 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
│   │
│   └──models         <- Scripts that contain the models and their code
│
└── tox.ini            <- tox file with settings for running tox; see tox.readthedocs.io

Project based on the cookiecutter data science project template. #cookiecutterdatascience

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