This is an implementation of a fully connected neural network in NumPy. The network may be trained by the backpropagation algorithm in an on-line fashion.
The code has been tested.
- Python
- NumPy
This script has been written with PYPY in mind. Use their jit-compiler to run this code blazingly fast.
To run the code, navigate into the project folder and execute the following command in the terminal:
$ python main.py
To train the network on a custom dataset, you will have to alter the dataset specified in the main.py
file. It is quite self-explanatory.
- Implemented with matrix operation to improve performance.
- PYPY friendly (requires pypy-numpy).
- Three activation functions: tanh, sigmoid and the linear activation function.