Q:

How to create a neural network for finding geolocation

There was made an order of food in a certain time from a certain place. I have the following info:

Location - delivery address
Date and time of the order
Day of the week
The weather on that day

The aim of that neural network is to train it and then predict the future orders. E.g. the places where the most of the orders will be tomorrow.
What type of the neural network should be used to make achieve that goal?
What framework or lib is better to be used for such kind of neural network?
It would be great to have an example of a working similar neural network!

A:

Your data is a time series and such can be tackled by e.g. a Recurrent Neural Network (RNN). The popular choice here is LSTM.
You should consider what granularity your location system should have. The exact coordinates are irrelevant, you should translate it to address or, better yet, districts. You can try square grid, but something hand-crafted will work better. Visualise your training data, see how orders are clustering and based on this you could create districts.
Expect seasonality of various forms. Your ANN should for sure look at least at full month, if not a year (depending on climate). You can start with a week though. 

