ychen-nyu/convnn-cifar-10

classifier of 10 classes of objects by a convolution neural network

Image Classification of the CIFAR-10 dataset by a Convolution Neural Networ-CIFAR-10

Build an image classifier by a convolution neural network and perform training/testing in the AWS AMI instance.

Getting Started

The dataset CIFAR-10 is downloaded into the linux server from CIFAR-10 unpacked and read into the numpy.array

Prerequisites

AWS AMI Ubuntu 16.04 with tensorflow, keras pre-installed. A jupyter notebook server is configured on the Linux server by the following tutorial from AWS .

The notebook is opened in the local linux machine and computation is done by the server.

Performance

Training performance with the simple ConvNN can reach ~90% accuracy but the testing performance reaches ~70%. The 20% gap denotes the training dataset has overfit issues.