kevinkarnani / CIFAR-10-Classifier

CIFAR-10-Classifier

Introduction

Four deep learning models (ANN, MLP, CNN, and GAN) were implemented to classify images from the CIFAR-10 dataset.

Getting Started

Prerequisites

The following dependencies are required:

• numpy

• os

• pickle

• concurrent.futures

• tqdm

  • trange

• skimage

  • transform

• sklearn

  • accuracy_score

• softmax

  • Softmax

• matplotlib

  • pyplot

If using Anaconda with Python 3.8+, everything above is included except tqdm and concurrent.futures.

To add tqdm, run:

conda install -c conda-forge tqdm

To add concurrent.futures, run:

conda install -c anaconda futures

Else, individually install these libraries using pip install.

Running The Python Scripts and Notebooks

Given the .idea folder, the project can be set up in PyCharm Professional. However, using other IDEs such as Jupyter Notebook or JupyterLab will also suffice.

Authors

• Kevin Karnani

• Saadiya Allahbaksh

• Ritik Ghanshani

• Anthony Goncharenko