Install requirements with virtualenv.
First run load.py
normalize and add bias to inputs. It then reads inputs and targets into binary files. Targets get processed into arrays with a '1' indicating target.
Run train.py
. Takes 2 arguments: learning rate and epochs.
Both files assume /MNIST/
in repo directory.
pip3 install virtualenv
virtualenv -p python3 env
This will install virtualenv using pip3 and create a an env
folder that will contain the libraries it uses.
source env/bin/activate
This will put your shell into the virtual environment where you will have the libraries brought it. (Note: fish `. env/bin/activate.fish*)*
pip3 install -r requirements.txt
This will install the libraries that are found in requirements.txt
When you are done working, use deactivate
to get out of the virtual environment
sort arrays. (ie is it x[i][j] or other way around?)
Can weight updates be done with matrix ops? YES
Test arrays with Python3 interpreter
Working out algorithm