How to handle string features in a neural network I am new to ANNs. How to handle features whicvh consist of strings? E.g. if I have group featire which are different groups conatining differnt capital Leters and numbers.

Now I have the train data set containing all such important features. 

My first guess is just to replace stings with numbers. But you have different uncorrelated groups of strings like the category or the manufacturer.
Does the string add any useful data? No. You should replace categories by id's for sure, and manufacturers as well. Why would having uncorrelated groups of strings stop you from giving each an id? 

So Google = 0, Apple = 1, etc. But that doesn't mean that a category can't have id 0 or 1. This is a different input, so these should start at 0 too: Books = 0, Electronics = 1. You still have to normalize these id's for your network ofcourse (value = id / maxId). 

This might be useful: https://github.com/cazala/synaptic/wiki/Normalization-101