Description
DFFML aims to be the easiest and most convenient way to use Machine Learning.
- Its a machine learning distribution. Providing you access to a set of popular
machine learning libraries guaranteed to work together.
- Its a AI/ML Python library, command line application, and HTTP service.
- You give it your data and tell it what kind of model you want to train. It
creates a model for you.
- If you want finer grained control over the model, you can easily do so by
implementing your own model plugin.
- We make it easy to use and deploy your models.
- We provide a directed graph concurrent execution environment with managed
locking which we call DataFlows.
- DataFlows make it easy to generate datasets or modify existing datasets for
rapid iteration on feature engineering.
Data Flow Facilitator for Machine Learning (dffml) alternatives and similar packages
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Optimize your datasets for ML
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest.
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Popular Comparisons
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Data Flow Facilitator for Machine Learning (dffml)vstensorflow
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README
Data Flow Facilitator for Machine Learning (dffml)
Mission Statement
DFFML aims to be the easiest and most convenient way to use Machine Learning.
Its a machine learning distribution. Providing you access to a set of popular machine learning libraries guaranteed to work together.
Its a AI/ML Python library, command line application, and HTTP service.
You give it your data and tell it what kind of model you want to train. It creates a model for you.
If you want finer grained control over the model, you can easily do so by implementing your own model plugin.
We make it easy to use and deploy your models.
We provide a directed graph concurrent execution environment with managed locking which we call DataFlows.
DataFlows make it easy to generate datasets or modify existing datasets for rapid iteration on feature engineering.
Documentation
Documentation for the latest release is hosted at https://intel.github.io/dffml/
Documentation for the master branch is hosted at https://intel.github.io/dffml/master/index.html
Contributing
The contributing page will guide you through getting setup and contributing to DFFML.
Help
- Ask a question via an issue
- Send an email to [email protected]
- You can subscribe to the users mailing list here https://lists.01.org/postorius/lists/dffml-users.lists.01.org/
- Ask a question on the Gitter chat
License
DFFML is distributed under the [MIT License](LICENSE).
Legal
This software is subject to the U.S. Export Administration Regulations and other U.S. law, and may not be exported or re-exported to certain countries (Cuba, Iran, Crimea Region of Ukraine, North Korea, Sudan, and Syria) or to persons or entities prohibited from receiving U.S. exports (including Denied Parties, Specially Designated Nationals, and entities on the Bureau of Export Administration Entity List or involved with missile technology or nuclear, chemical or biological weapons).
*Note that all licence references and agreements mentioned in the Data Flow Facilitator for Machine Learning (dffml) README section above
are relevant to that project's source code only.