Mathematics, Calculus, Tensor, Deep Learning, Machine Learning.
layer output_input = np.dot(hidden_output, self.weights_hidden_output) + self.biases_output predicted_output = 1 / (1 + np.exp(-output_input)) # Sigmoid activation function return predicted_output # Create a sample input input_data = np.array([[0, 1]]) # Initialize the neural network with 2 input