Skip to content

Using TensorFlow and scikit-learn to classify counties in the U.S. presidential election based on given features. Placed 5th in the class overall (CS 4780 - Machine Learning).

License

Notifications You must be signed in to change notification settings

JSun14/election-county-prediction

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

96 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

election-county-prediction

cs 4780 final project - We will be working with Tensorflow for this project.

Virtual Env

This will make sure that everyone is working on the same python environment so that we don't run into issues there.

Assuming Python 3.6.9 or greater:

First setup a virtual environment

python3 -m venv venv

Activate the virtual environment, this changes the env just a local copy of python

. venv/bin/activate

Install the same set of modules that every one else is using:

pip install -r ureq.txt

Post Install - How to do daily work

You will need to load into the virtual environment everyday when coding.

. venv/bin/activate

You might also need to change which python you're using. Do not use your system install, use the venv python. You can select the right version of python in the top right.

About

Using TensorFlow and scikit-learn to classify counties in the U.S. presidential election based on given features. Placed 5th in the class overall (CS 4780 - Machine Learning).

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 100.0%