GitHub - kvfairchild/MNIST-CNN: From-scratch CNN for use with the MNIST dataset. Two convolutional layers, two max pooling layers, one fully connected layer, and AdaGrad optimizer.

MNIST CNN

From-scratch CNN with two convolutional layers, two max pooling layers, one fully connected layer, and AdaGrad optimizer.

main.py: main file to init and run network
config.py: set net and training parameters (filter dimensions, learning rate, etc.)
MNIST_file_parser.py: parse MNIST files
initialize.py: initalize network (truncated normal distribution)
run.py: train and test network on MNIST dataset
network.py: CNN (feedforward & backprop)
optimize.py: contains AdaGrad optimizer

Typical training output:

Batch 50/500 of Epoch 1/1: Cost: 0.35, Batch: 91% accuracy, Epoch: 85% accuracy

Typical test output:

#50/10000: 7 | 7  OK
#51/10000: 8 | 3  X

To run:

./main.py

Name		Name	Last commit message	Last commit date
Latest commit History 3 Commits
nodenet		nodenet
MNIST_file_parser.py		MNIST_file_parser.py
README.md		README.md
__init__.py		__init__.py
main.py		main.py