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Experimentation with Neural Networks, as well as recommender systems related to movies.

Jupyter Notebook 77.93% Python 22.07%
neural-networks regressor classifier recommender-system

neural-networks's Introduction

Neural Networks and Recommender Systems

About

This project was done during my time studying in the CS 340: Machine Learning course run by Dr. Mike Gelbart and co. Much of the base code can be attributed to him and his team. Experimentations with listed items were done by Matthew Hounslow.

Contents

In this repo you will find some interesting experimentations with sklearn's Neural Network regressors and classifiers on sklearn data. All code is written in Python 3.6. This repo comes with sample data that the aforementioned techniques can be employed on. Errors and analysis are printed to the console.

Dependencies

  • numpy
  • Sklearn
  • scipy
  • matplotlib

Running the project

In order to run the project, use python3 main.py -q <topic-number> where represents the section in main.py. Each section number pertains to a different technique in this case. More comments will be added to these files in the future to give greater clarity.
s Experimentation with Neural Networks, as well as recommender systems related to movies.

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