Simple text recognition with neural network In my attempt at trying to learn neural network and machine learning I'm am trying to create a simple neural network which can be trained to recognise one word from a given string (which contains only one word). So in effect if one where to feed it a string containing the trained word but spelled wrong the network would be able to still recognise the word. Can anybody help me with some pseudo code or a start of a code. Or a general explanation of how to to this because I have read like 6 articles and 8 example projects and still have no clue how to do this
If I'm reading it correctly, this question has nothing to do with optical character recognition. You want to create a system that takes a digital string of characters as input, then finds the best match from a predetermined list of words. That sounds like a task for if-then-else logic and dictionary lookup. It might be possible to use a neural net, but not easy.

A neural net takes a fixed number of inputs, each of which are a value between zero and one. A major hurdle is that you probably want variable-sized inputs. Another hurdle is that you'll need to code the inputs some way onto numbers.

These hurdles can be overcome but they are tipoffs that neural networks aren't well-suited for the task.