Python implementation of simple neural networks for XOR gates

• Implemented without any external library including Numpy and other machine learning libraries.
• The neural networks comprise input, hidden, output layers.
• The only hidden layer has 2 hidden units with bias.
• The weights are updated by simple stochastic gradient descent algorithm which makes training unstable.
• Training might fail with about 10% chance due to randomly initialized weights and the poor ability of SGD.
• SGD with MSE in PyTorch also failed to train this networks while Adam or other advanced optimizers made it.
• Training is sensitive to the learning rate. 1.0 ~ 5.0 is recommended.