A simple feed forward neural network implementation for predicting handwritten digits.
The model is comprised of three neural layers:
- 784 neurons in input layer
- 200 neurons in hidden layer
- 10 neurons in output layer
The activation function is sigmoid.
Training and testing was done in Python with Anaconda package.
