Blog post is here
If you want an intro to neural nets and the "long version" of what this is and what it does, read my blog post.
Data can be downloaded here. Many thanks to ThinkNook for putting such a great resource out there.
You need Python 2 to run this project; I also recommend Virtualenv and iPython.
Run pip install
to install everything listed in requirements.txt
.
You need to train your net once, and then you can load those settings and use it whenever you want without having to retrain it.
Change line 10 of makeModel.py
to point to wherever you downloaded your data as a CSV.
Then run Python makeModel.py
(or, if you're in iPython, run makeModel.py
). Then go do something else for the 40-60 minutes that it takes to train your neural net.
When creating the net finishes, three new files should have been created: dictionary.json
, model.json
, and model.h5
. You will need these to use the net.
To use the net to classify data, run loadModel.py
and type into the console when prompted. Hitting Enter without typing anything will quit the program.