I am trying to build and train a machine learning data science algorithm that correctly predicts what president won in what county. I have the following information for training data.Total population Median age % BachelorsDeg or higher Unemployment rate Per capita income Total households Average household size % Owner occupied housing % Renter occupied housing % Vacant housing Median home value Population growth House hold growth Per capita income growth WinnerI am new to the field and this is my first time building an artificial neural network and I don't know what to do to start (so forgive me if my question is extremely broad). What I have done so far is read the wikipedia page for artificial neural networks. What I want to do next is implement supervised learning using the training data.I would appreciate any help getting started. Please let me know if you have used any good tutorials or libraries to help build something similar. I was thinking of using the library Lasagne.A few specific questions I have as I tried to use Lasagne - What is the error I am to calculate when building an algorithm using training data? How many layers do I need and what does each layer signify?
How to build a supervised artificial neural network?
machine learning;neural network;algorithms;supervised learning