Comparison-performance-between-CNN-architectures | Comparison performance between CNN architectures

 by   heymadscientist Jupyter Notebook Version: Current License: MIT

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kandi X-RAY | Comparison-performance-between-CNN-architectures Summary

kandi X-RAY | Comparison-performance-between-CNN-architectures Summary

Comparison-performance-between-CNN-architectures is a Jupyter Notebook library. Comparison-performance-between-CNN-architectures has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

Comparison performance between CNN architectures to classify galaxies by morphology
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              Comparison-performance-between-CNN-architectures has a low active ecosystem.
              It has 0 star(s) with 0 fork(s). There are 1 watchers for this library.
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              It had no major release in the last 6 months.
              Comparison-performance-between-CNN-architectures has no issues reported. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Comparison-performance-between-CNN-architectures is current.

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              Comparison-performance-between-CNN-architectures has no bugs reported.

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              Comparison-performance-between-CNN-architectures has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

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              Comparison-performance-between-CNN-architectures is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

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              Comparison-performance-between-CNN-architectures 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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            Install Comparison-performance-between-CNN-architectures

            These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
            First clone the repository.

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