kandi X-RAY | Deep-Learning Summary
kandi X-RAY | Deep-Learning Summary
Deep-Learning is a Python library. Deep-Learning has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However Deep-Learning build file is not available. You can download it from GitHub.
Deep-Learning
Deep-Learning
Support
Quality
Security
License
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Support
Deep-Learning 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.
Deep-Learning has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of Deep-Learning is current.
Quality
Deep-Learning has no bugs reported.
Security
Deep-Learning has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
Deep-Learning is licensed under the GPL-3.0 License. This license is Strong Copyleft.
Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.
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Deep-Learning releases are not available. You will need to build from source code and install.
Deep-Learning has no build file. You will be need to create the build yourself to build the component from source.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of Deep-Learning
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of Deep-Learning
Deep-Learning Key Features
No Key Features are available at this moment for Deep-Learning.
Deep-Learning Examples and Code Snippets
No Code Snippets are available at this moment for Deep-Learning.
Community Discussions
No Community Discussions are available at this moment for Deep-Learning.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install Deep-Learning
You can download it from GitHub.
You can use Deep-Learning 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.
You can use Deep-Learning 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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