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Liquid ML

Updated May 17, 2019
  

Liquid ML is a pioneering framework to interconnect enterprise analytics with collaborative data science and machine learning.

Based on the Cloud-Assisted Meta programming (CAMP) paradigm, the framework allows the usage of Currently Best Fitting (CBF) algorithms. Before code interpretation / compilation the concrete algorithms, that implement the CBF specifications, are automatically chosen from local and public catalog servers, that host and deploy the concrete algorithms. Thereby the specification is constituted by a unique algorithm category, a data domain and a metric, which substantiates the meaning of Best Fitting within the respective algorithm- and data context. An example is the average prediction accuracy within a fixed set of gold standard samples of the data domain (e.g. latin handwriting samples, spoken word samples, TCGA gene expression data, etc.).

The Liquid ML framework allows the implementation of cutting edge enterprise analytical applications, that are automatically kept up-to-date and therefore minimize their maintenance costs. Also the Liquid ML framework facilitates the publication, application, sharing and comparison of algorithms, within and between workgroups.

Linked repositories: nemoa, pandora, flib, motley

Motley

Updated May 17, 2019
  

Motley is a planed catalog server for algorithm storage and evaluation and based on GIT. Motley aims to serve as an algorithm catalog to allow the usage of abstract currently best fitting (CBF) algorithms, as required by the Cloud-Assisted Meta Programming (CAMP) paradigm.

Thereby Motley is required to host and deliver algorithms as well es to cyclically evaluate and index them with respect to their corresponding metrics, using Nemoa. An example for such a metric would be the average prediction accuracy within a fixed set of gold standard samples of the respective domain of application (e.g. latin handwriting samples, spoken word samples, TCGA gene expression data, etc.). Consequently Motley is also required to host or connect these samples by using Pandora.

Motley is free and open source software and actively developed as part of the Liquid ML framework at Frootlab.

Linked repositories: motley

Nemoa

Updated May 17, 2019
  

Nemoa is a machine learning- and data analysis framework, that implements the Cloud-Assisted Meta Programming (CAMP) paradigm.

The key goal of Nemoa 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 Nemoa orchestrates established Python frameworks like TensorFlow® and SQLAlchemy and dynamically extends their capabilities by community driven algorithms (e.g. for probabilistic graphical modeling, machine learning and structured data-analysis). Thereby Nemoa allows client-side implementations to use abstract currently best fitting (CBF) algorithms. During runtime the concrete implementation of CBF algorithms are chosen server-sided by category and metric. An example for such a metric would be the average prediction accuracy within a fixed set of gold standard samples of the respective domain of application (e.g. latin handwriting samples, spoken word samples, TCGA gene expression data, etc.).

Nemoa is free and open source software and actively developed as part of the Liquid ML framework at Frootlab.

Linked repositories: nemoa

Pandora

Updated May 17, 2019
  

Pandora is a universal database proxy and SQL database engine, that implements high performance and security requirements of enterprise data analytics.

The primary goal of Pandora is to provide a unified (universal) data interface for machine learning- and data analysis applications, to facilitates their integration into existing operational data landscapes. This comprises RDBMS architectures from IBM, Oracle, SAP, Microsoft and many others as well as flat file databases and statistical data generators. Currently planed features of Pandora include an DBAPI 2.0 interface with full SQL:2016 support, a vertical data storage manager and realtime encryption.

Pandora is free and open source software and actively developed as part of the Liquid ML framework at Frootlab.

Linked repositories: pandora

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