neural_nets | scipy implementation of neural networks

by ekgren Python Version: Current License: No License

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

kandi X-RAY | neural_nets Summary

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

Python with numpy/scipy implementation of neural networks for learning and experimenting.

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Quality

Security

License

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Support

neural_nets 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.

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

It has a neutral sentiment in the developer community.

The latest version of neural_nets is current.

Quality

neural_nets has no bugs reported.

Security

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

License

neural_nets does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

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

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

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neural_nets Key Features

No Key Features are available at this moment for neural_nets.

neural_nets Examples and Code Snippets

No Code Snippets are available at this moment for neural_nets.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install neural_nets

You can download it from GitHub.
You can use neural_nets 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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