backpropagation work. how? : I created my first simple Neural Net on the paper. It has 5 inputs(data - float number from 0.0 to 10.0) and one output. Without hidden layers. For example at start my weights = [0.2, 0.2, 0.15, 0.15, 0.3]. Result should be in range like input data(0.0 - 10.0). For example network returned 8 when right is 8.5. How backprop will change weights? I know how grad.descent works but I can't understand how i should choose parameters of partial derivative. Help, please. I can elaborate something if you need.