I am a beginner with DL. I did some tutorials and I know the basics of TensorFlow. But I have a problem understanding how to construct more advanced NNs.
Let's say I have 6 inputs and a list of 500 names from which you can pick any, but only 6 at the time. The output should be one value between $0.0$ and $1.0$.
My question is, how I can handle random order in inputs? In inputs 1-6 you have names ABCDEF and the output score is 0.7. I need the same output if input will be in order CEDBFA. How can I handle this? Should I make random shuffle on inputs during training, or should I make for every output value 500D binary vector-like $[0,0,1,0,1,...,0,1,0,0,0]$, where index position in the array is the corresponding token of name and then feed it in 500 inputs? Or there is some better way?