1---Single input
Let's think about how single neurons work in data sets such as 80cereals.
Suppose a model:
Input：'sugars' （grams of sugars per serving）
Output：'calories' （calories per serving）
w：2.5
b：90
Looking back at the previous section(Deep Learning1), we can see the following images
In short, calories=sugars*2.5+90*1=5*2.5+90=102.5
2---Multiple inputs
80cereals isn't just 'sugars', it's something else, so how can we expand our model to include more things?
We can just add more input connections to the neuron.To find the output, we would multiply each input to its connection weight and then add them all together.
The formula for this neuron would be:
????=????0????0+????1????1+????2????2+????
A linear unit with two inputs will fit a plane, and a unit with more inputs than that will fit a hyperplane.