The simplest neural network (simplified).
You input a set of properties(first column). Then you weightedly add all of them a number of times(with DIFFERENT weights)(first set of lines). Then you apply a non-linearity to it, e.g. 0 if negative, keep the same otherwise(not shown).
You repeat this with potentially different numbers of outputs any number of times.
Then do this again, but so that your number of outputs is the dimension of your desired output. E.g. 2 if you want the sum of the inputs and their product computed(which is a fun exercise!). You may want to skip the non-linearity here or do something special™
The simplest neural network (simplified). You input a set of properties(first column). Then you weightedly add all of them a number of times(with DIFFERENT weights)(first set of lines). Then you apply a non-linearity to it, e.g. 0 if negative, keep the same otherwise(not shown).
You repeat this with potentially different numbers of outputs any number of times.
Then do this again, but so that your number of outputs is the dimension of your desired output. E.g. 2 if you want the sum of the inputs and their product computed(which is a fun exercise!). You may want to skip the non-linearity here or do something special™