music-auto_tagging-keras | Music auto-tagging models | Machine Learning library
kandi X-RAY | music-auto_tagging-keras Summary
kandi X-RAY | music-auto_tagging-keras Summary
music-auto_tagging-keras is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, Keras applications. music-auto_tagging-keras has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However music-auto_tagging-keras build file is not available. You can download it from GitHub.
Music auto-tagging models and trained weights in keras/theano
Music auto-tagging models and trained weights in keras/theano
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Quality
Security
License
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Support
music-auto_tagging-keras has a low active ecosystem.
It has 603 star(s) with 144 fork(s). There are 32 watchers for this library.
It had no major release in the last 6 months.
There are 7 open issues and 39 have been closed. On average issues are closed in 47 days. There are 1 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of music-auto_tagging-keras is current.
Quality
music-auto_tagging-keras has 0 bugs and 0 code smells.
Security
music-auto_tagging-keras has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
music-auto_tagging-keras code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
music-auto_tagging-keras 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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music-auto_tagging-keras releases are not available. You will need to build from source code and install.
music-auto_tagging-keras has no build file. You will be need to create the build yourself to build the component from source.
Installation instructions are not available. Examples and code snippets are available.
Top functions reviewed by kandi - BETA
kandi has reviewed music-auto_tagging-keras and discovered the below as its top functions. This is intended to give you an instant insight into music-auto_tagging-keras implemented functionality, and help decide if they suit your requirements.
- Build a convnet model
- Generate a VGG model
- Creates a convolutional model
Get all kandi verified functions for this library.
music-auto_tagging-keras Key Features
No Key Features are available at this moment for music-auto_tagging-keras.
music-auto_tagging-keras Examples and Code Snippets
No Code Snippets are available at this moment for music-auto_tagging-keras.
Community Discussions
Trending Discussions on music-auto_tagging-keras
QUESTION
keras 1.1 version giving value error on importing it on windows 10 after installation (typo error in configuration file )
Asked 2018-Feb-11 at 09:28
i installed keras 1.1 version and theano 0.8.2 version on a python2.7 anaconda virtualenvironment on windows 10 machine to run this repo the installation went fine but when i try to import keras in python shell it gives me this error
...ANSWER
Answered 2018-Feb-10 at 17:12Anaconda3 means it has python3.x version, so i think making a virtual environment with anaonda3 and python2.7 will generate error. try making a virtual environment will python 3.x. hope it helps.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install music-auto_tagging-keras
You can download it from GitHub.
You can use music-auto_tagging-keras 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 music-auto_tagging-keras 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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