Uses deep learning to classify images from CIFAR-10 dataset
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README.md
dlnd_image_classification.html
dlnd_image_classification.ipynb
helper.py
problem_unittests.py

README.md

deep-learning

Project 2 submission for Udacity's Deep Learning Nanodegree program

##Description

In this project, you'll classify images from the CIFAR-10 dataset. The dataset consists of airplanes, dogs, cats, and other objects. The dataset will need to be preprocessed, then train a convolutional neural network on all the samples. You'll normalize the images, one-hot encode the labels, build a convolutional layer, max pool layer, and fully connected layer. At then end, you'll see their predictions on the sample images.

Initial files can be found here