This repository contains some code for you to get started with keras with a few simple datasets.
- This code runs on Python 3.5 and Keras 2.0.4 and has been tested on Ubuntu 16.04.
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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.
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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.
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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.
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The code can be run in train or test mode.
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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.