This repository contains a VNet-like architecture for time series classification tasks. The model is designed to classify time series data, in our case accelerometry data, using a VNet-inspired architecture.
To try the model, we generate fake accelerometry data. The generated data is used as input for training and evaluation.
To use this repository, follow these steps:
- Clone the repository:
git clone https://github.com/iamhaingo/vnet.timeseries.git - Run the script:
python main.py
Feel free to modify the code and experiment with different datasets to suit your needs.
Contributions are welcome! If you find any issues or have suggestions for improvements, please open an issue or submit a pull request.
This project is licensed under the MIT License. See the LICENSE file for more details.