Skip to main content

Train MNIST with different models using Tensorflow.

Project description

# netra

Train & query MNIST dataset with different models using Tensorflow.

# Installation

$ pip install netra

# Usage

Help:

$ netra –help

Querying model:

$ netra query -i https://i.imgur.com/GbreNv2.png $ netra query -i /foo/bar/foo.png

Training model:

$ netra train –model regression $ netra train –model regression –epochs 1000 –batch_size 100 $ netra train -m regression -e 1000 -b 100

# Sample output:

![netra](https://user-images.githubusercontent.com/4463796/26892117-e1a77a34-4bd4-11e7-91d2-11af0d1294f7.png)

![netra2](https://user-images.githubusercontent.com/4463796/26892600-773b27fc-4bd6-11e7-9bfd-38b60b88b8bf.png)

Project details


Download files

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

Source Distribution

netra-0.1.2.tar.gz (4.4 kB view details)

Uploaded Source

File details

Details for the file netra-0.1.2.tar.gz.

File metadata

  • Download URL: netra-0.1.2.tar.gz
  • Upload date:
  • Size: 4.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for netra-0.1.2.tar.gz
Algorithm Hash digest
SHA256 02055cb576ff2bd8678b318332eed212fc34c9032edee464ff48faf6765a2f50
MD5 3acbc69c8705b662904b2fe2a6c6949c
BLAKE2b-256 b946a8c8155471ae41b007ebbb708d58d283aa4c9e168c58ca3e2ce151a3e045

See more details on using hashes here.

Supported by

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