Skip to main content

CNN and softmax regression classifiers for MNIST digits

Project description

Models

mnist-cnn

CNN classifier for MNIST

Operations

evaluate

Evaluate a trained CNN

train

Train the CNN

Flags
batch-size

Number of images to include in a training batch (default is 100)

epochs

Number of epochs to train (default is 10)

mnist-samples

Sample MNIST images

Operations

prepare

Generate a set of sample MNIST images

Flags

count

Number of images to generate (default is 100)

mnist-softmax

Softmax regression classifier for MNIST

Operations

evaluate

Evaluate a trained softmax regression

train

Train the softmax regression

Flags
batch-size

Number of images to include in a training batch (default is 100)

epochs

Number of epochs to train (default is 10)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

gpkg.mnist-0.3.1.1-py2.py3-none-any.whl (10.7 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file gpkg.mnist-0.3.1.1-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for gpkg.mnist-0.3.1.1-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 e4599e7b5e156a980a3c4472ff679b5fe4c1ad94dbc720bb5dacc166e3b88b56
MD5 283206be77df4c31f0d48fc9317fff24
BLAKE2b-256 82fc8a25c458a47f16f099eef4d5f48bf991759dd49f0f0fc28870035b8b3308

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page