@@ -26,5 +26,16 @@ where `/home/.../` has to be changed to the path this repository is located in.
## Usage
The basic theory behind neural networks is explained in [docs/basisc.md](doc/basics.md).
Here you can find some additional references and links to get you going on your in-depth neural network adventure as well.
Besides the theory, I added some scripts to give you a basic coding structure and show you how to employ neural networks with [PyTorch](https://pytorch.org/).
The following table gives you an overview of the scripts and what they do.
| File | Description |
| --- | --- |
| [app/function_approximation.py](app/function_approximation.py) | A simple benchmark on how to approximate a 2D sine function with a neural network, broken down to a few simple steps. The code used for the steps can be found in [src/approximation.py](src/approximation.py). |
| [app/mnist_image_classification.py](app/mnist_image_classification.py) | A simple benchmark for image classification using the MNIST data set. The code used for the steps can be found in [src/mnist.py](src/mnist.py). |
## License
This software runs under the GNU General Public License 3.0.
