ACC_NAS | Accelerating multi-objective neural architecture search

by mohyunho Python Version: Current License: Apache-2.0

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

kandi X-RAY | ACC_NAS Summary

ACC_NAS is a Python library. ACC_NAS 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.

Accelerating multi-objective neural architecture search for remaining useful life prediction.

Support

Quality

Security

License

Reuse

Support

ACC_NAS has a low active ecosystem.

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

It had no major release in the last 6 months.

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

It has a neutral sentiment in the developer community.

The latest version of ACC_NAS is current.

Quality

ACC_NAS has no bugs reported.

Security

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

License

ACC_NAS 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

ACC_NAS 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 are not available. Examples and code snippets are available.

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ACC_NAS Key Features

No Key Features are available at this moment for ACC_NAS.

ACC_NAS Examples and Code Snippets

No Code Snippets are available at this moment for ACC_NAS.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install ACC_NAS

You can download it from GitHub.
You can use ACC_NAS 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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