Artificial neural networks
## defining architecture def softmax(a): ea = np.exp(a) return ea/np.sum(ea,axis=1,keepdims=True) class NeuralNetwork: #constructo def __init__(self,input_size,layers,output_size): np.random.seed(0)# so that we are able to reproduce the results every time model = {} model['W1'] = np.random.randn(input_size,layers[0]) model['b1'] = np.zeros((1,layers[0])) model['W2'] = np.random.randn(layers[0],layers[1]) model['b2'] = np.zeros((1,layers[1])) model['W3'] = np.random.randn(layers[1],output_size) model['b3'] = np.zeros((1,output_size)) self.mod...