workshop-traffic-signs

by pkern90 Jupyter Notebook Version: Current License: No License

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

kandi X-RAY | workshop-traffic-signs Summary

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

workshop-traffic-signs

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Quality

Security

License

Reuse

Support

workshop-traffic-signs has a low active ecosystem.

It has 0 star(s) with 1 fork(s). There are 3 watchers for this library.

It had no major release in the last 6 months.

workshop-traffic-signs has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of workshop-traffic-signs is current.

Quality

workshop-traffic-signs has no bugs reported.

Security

workshop-traffic-signs has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

workshop-traffic-signs 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

workshop-traffic-signs releases are not available. You will need to build from source code and install.

Installation instructions, examples and code snippets are available.

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workshop-traffic-signs Key Features

No Key Features are available at this moment for workshop-traffic-signs.

workshop-traffic-signs Examples and Code Snippets

No Code Snippets are available at this moment for workshop-traffic-signs.

Community Discussions

No Community Discussions are available at this moment for workshop-traffic-signs.Refer to stack overflow page for discussions.

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

Vulnerabilities

No vulnerabilities reported

Install workshop-traffic-signs

Clone or download this repository
Get the data
Setup your environment
We will use python 3.5 with the following packages:. The easiest way to get started is by installing anaconda. Anaconda allows to create virtual environments to keep everything nice an clean. After installing anaconda your command line tool of choice and execute the following statements.
jupyter
NumPy
scikit learn
matplotlib
seaborn
tqdm
TensorFlow v1+
Keras

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 .

Find more information at: