TensorFlowPractice | TensorFlowPractice

by caelanyang Python Version: Current License: Apache-2.0

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

kandi X-RAY | TensorFlowPractice Summary

TensorFlowPractice is a Python library. TensorFlowPractice has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However TensorFlowPractice build file is not available. You can download it from GitHub.

TensorFlowPractice

Support

Quality

Security

License

Reuse

Support

TensorFlowPractice has a low active ecosystem.

It has 0 star(s) with 0 fork(s). There are no watchers for this library.

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of TensorFlowPractice is current.

Quality

TensorFlowPractice has no bugs reported.

Security

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

License

TensorFlowPractice is licensed under the Apache-2.0 License. This license is Permissive.

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

Reuse

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

TensorFlowPractice has no build file. You will be need to create the build yourself to build the component from source.

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TensorFlowPractice Key Features

No Key Features are available at this moment for TensorFlowPractice.

TensorFlowPractice Examples and Code Snippets

No Code Snippets are available at this moment for TensorFlowPractice.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install TensorFlowPractice

You can download it from GitHub.
You can use TensorFlowPractice like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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