Single-Layer-ANN
An implementation of a single layer neural network in Python. This is a part of an article that I contributed to GeekforGeeks technical blog. You can check it out here to understand the implementation in detail and know about the training process.
Dependencies
You need to install NumPy library on your system to run the code. To know how to install NumPy, follow the instructions here according to your platform: https://docs.scipy.org/doc/numpy-1.10.1/user/install.html.
If you're on Ubuntu/Debian platform like me, you can simply enter the following in the terminal:
$ sudo apt-get install python-numpy
Running the neural network
Clone this repository in your system and go to the root directory of the cloned copy i.e. ~/Single-Layer-ANN
Now, just run ann.py in your terminal:
$ python ann.py
To change the training example, you need to modify the training set for the network which is specified by numpy arrays named as inputs and outputs in the code; they basically represent input values and expected output for a given combination of inputs respectively.
Note: Since this is a single layer network, it can only work with linearly separable functions or patterns e.g. AND and OR. Trying to play with this network using XOR would be a waste of time. :)
License
This code is distributed under the MIT license.