MNIST

by ditat-llc Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions Vulnerabilities Install Support

kandi X-RAY | MNIST Summary

MNIST is a Python library. MNIST has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This repository demonstrates using Paperspace Gradient to train and deploy a deep learning model to recognize handwritten characters, which is a canonical sample problem in machine learning. We build a convolutional neural network to classify the MNIST dataset using the tf.data, tf.estimator.Estimator, and tf.layers APIs.

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MNIST has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

MNIST has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of MNIST is current.

Quality

MNIST has no bugs reported.

Security

MNIST has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

MNIST is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

MNIST releases are not available. You will need to build from source code and install.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

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MNIST Key Features

No Key Features are available at this moment for MNIST.

MNIST Examples and Code Snippets

No Code Snippets are available at this moment for MNIST.

Community Discussions

No Community Discussions are available at this moment for MNIST.Refer to stack overflow page for discussions.

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install MNIST

Users sometimes run into local machine environment issues when trying to use Python. A common solution for this is to create and use a Python virtual environment to run Python from within. To do so:.
Create and activate a Python virtual environment (we recommend using python3.7+):
Install the required Python packages:

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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