def forward(self, inputData):
		"""
		Compute activation by propagating input forward
		@param inputData input (excl. bias)
		"""
		self.activations[0][1:] = inputData # copy input data
		for el in range(1, self.numLayers):
			z = numpy.dot(self.weights[el-1], self.activations[el-1])
			self.activations[el][1:] = sigmoid(z)
			self.activations[el][0] = 1.0

		return self.getOutput()

		Compute activation by propagating input forward
		@param inputData input (excl. bias)
		
recipes/Python/578932_Teach_your_computer_a_few_tricks/recipe-578932.py