Enterprise Machine-Learning and Predictive Analytics
Rian is a machine learning- and data analysis framework, that implements cloud-assisted meta programming (CAMP).
The key goal of Rian is to provide a long-term data analysis framework, which seemingly integrates into existing enterprise data environments and thereby supports collaborative data science. To achieve this goal Rian orchestrates established frameworks like TensorFlowÂ® and dynamically extends their capabilities by community driven algorithms (e.g. for probabilistic graphical modeling, machine learning and structured data-analysis).
Thereby Rian allows the client-side usage of abstract algorithms, that are specified with respect to their category, the used data type and an evaluation metric that determines their fitness. During runtime these abstract specifications are resolved server-sided from a code catalog, by a currently best fitting (CBF) algorithm.
For given category and application, the CBF algorithms are determined by their used metric. Examples for such metrices would be the prediction accuracies within a fixed set of gold standard samples of the respective domain of application (e.g. latin handwriting, spoken words, TCGA gene expression data, etc.).
Current Development Status
Rian currently is in Pre-Alpha development stage, which immediately follows the Planning stage. This means, that at least some essential requirements of Rian are not yet implemented.
Comprehensive information and installation support is provided within the online manual. If you already have a Python environment configured on your computer, you can install the latest distributed version by using pip:
$ pip install rian
Contributors are very welcome! Feel free to report bugs, ideas and feature requests to the issue tracker, provided by GitHub. Currently, as our team still is growing, we do not provide any Contribution Guide Lines. So, if you are interested to help or to join the team, we would be glad, to hear about you.
Rian is open source software and available free for any use under the GPLv3 license:
Â© 2019 Frootlab Developers: Patrick Michl <firstname.lastname@example.org> Â© 2013-2019 Patrick Michl
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