deeplearning_ng | python3

by venuktan Jupyter Notebook Version: Current License: No License

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

kandi X-RAY | deeplearning_ng Summary

deeplearning_ng is a Jupyter Notebook library. deeplearning_ng has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

python3.6.x + cudnn6.0 + CUDA8.0 + tensorflow-1.4.0.

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Quality

Security

License

Reuse

Support

deeplearning_ng 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.

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

It has a neutral sentiment in the developer community.

The latest version of deeplearning_ng is current.

Quality

deeplearning_ng has no bugs reported.

Security

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

License

deeplearning_ng 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

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

Installation instructions are available. Examples and code snippets are not available.

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deeplearning_ng Key Features

No Key Features are available at this moment for deeplearning_ng.

deeplearning_ng Examples and Code Snippets

No Code Snippets are available at this moment for deeplearning_ng.

Community Discussions

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

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

Vulnerabilities

No vulnerabilities reported

Install deeplearning_ng

python3.6.x + cudnn6.0 + CUDA8.0 + tensorflow-1.4.0.
Cause I found many people get many issues while installing tensorflow-gpu on windows, and there are many talks before tensorflow-1.4.0 shows like this on Stackoverflow.
You will not face problem above again thanks to tensorflow-1.4.0!
python3.6.x + cudnn6.0 + CUDA8.0 + tensorflow-1.4.0 work perfect!
Remember move files in cundnn to CUDA8.0 accordingly (you also do this in the past)!

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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