CIFAR-10 using CNNs

This project aims to predict the labels of the CIFAR-10 datset. This project uses Keras to implement deep learning. Almost all the code is in the form of IPython notebooks.
Final accuracy - 87.94%

Mis-classifications

Metric graphs

Dependencies

• Jupyter
• Keras
• Tensorflow
• Matplotlib
• Pickle

Contents

1. Helper - Helper functions which decode and fetch the data to the IPython notebooks
2. Basic - IPython notebook to test helper functions and list images in the dataset
3. Simple CNN - IPython notebook with a simple implementation of CNN taken from the Keras examples
4. Improved CNN - IPython notebook which uses a pure CNN network with image augmentations to implove the accuracy of the model
5. Model files (.h5) - Different saved models

Getting started

The quickest way to run these on a fresh Linux machine is to follow this tutorial:

Then clone this repo and start Jupyter Notebook:

git clone https://github.com/09rohanchopra/cifar10.git
cd cifar10
jupyter notebook

Tutorial

Feedback

If you have ideas or find mistakes please leave a note.

License

MIT