CIFAR_visual | convolutional neural network on the CIFAR-10 data

by SethEBaldwin Python Version: Current License: No License

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

kandi X-RAY | CIFAR_visual Summary

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

Train a convolutional neural network on the CIFAR-10 data and find image patches which maximally activate the filters

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Quality

Security

License

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Support

CIFAR_visual 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.

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

It has a neutral sentiment in the developer community.

The latest version of CIFAR_visual is current.

Quality

CIFAR_visual has no bugs reported.

Security

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

License

CIFAR_visual 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

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

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

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CIFAR_visual Key Features

No Key Features are available at this moment for CIFAR_visual.

CIFAR_visual Examples and Code Snippets

No Code Snippets are available at this moment for CIFAR_visual.

Community Discussions

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Vulnerabilities

No vulnerabilities reported

Install CIFAR_visual

You can download it from GitHub.
You can use CIFAR_visual 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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