Words as a input to network I want to build neural network, where my input will be a word(not a sentence). My set of words has many words with different lenght (number of chars). My idea to do it is transform chars to numbers using predefine dictionary, next use it as input. Number of neurons in input layer set as a number of chars in a longest word in my set. In vectors witch are shorter I'll fill them by zero.

My set of words looks that:

1. head
2. hello
3. butterfly
4. hotel
5. fly
6. spy


So for this set my input to netowrk should has 9 neurons. When I transform 'head', I will get vector with 4 numbers and 5 zeros. 

It's a good idea? Or maybe you have another better idea how input of this network could look.

EDIT:

My task is described here: ML model to transform words: 
And I want to build GAN as an answer suggest.
So this words will be my 'real words' and I want to generate fake words.
The simple way here is to make a one-hot over letters. So you will have many columns with ones and zeros. This may now be an input layer for your nn.