LearnKeras

This repository contains some code for you to get started with keras with a few simple datasets.

Compatibility

This code runs on Python 3.5 and Keras 2.0.4 and has been tested on Ubuntu 16.04.

Intro

The folder Intro contains the keras implementation for the analysis of the pima-indians-diabetes dataset.
It involves the prediction of a binary output variable using 8 input variables.
The code learnkeras1.py steps you through the training process and also shows you how to save your model checkpoint.
The code learnkeras2.py shows you how to load the above trained model and find accuracy.

CIFAR-10

The folder CIFAR-10 contains the code for classifying images into 10 categories of the famous CIFAR-10 dataset.
I have used a simple model architecture for easy understanding of code.
The code can be run in train or test mode.
To run in train mode, type python cifar10.py --mode train. This trains the model and saves the checkpoint in the folder. It will also make predictions on test data and print the accuracy.
To run in test mode, type python cifar10.py --mode test. This will output the test accuracy using weights from the checkpoint saved.
Download the checkpoint for 10 epochs here.