Hyland UK Operations Limited

Gethin Paul James

Tiago Filipe Dias Cardoso

Pedro Miguel Dias Cardoso

Andrei Nechaev

Isabel Maria Malheiro De Oliveira Novais Machado

Various embodiments are generally directed to techniques for intuitive machine learning (ML) development and optimization, such as for application in a content services platform (CSP), for instance. Many embodiments include a ML model developer and a ML model evaluator to provide a graphical user interface that guides ML layman in developing, evaluating, implementing, managing, and/or optimizing ML models. Some embodiments are particularly directed to a common interface that provides a step-by-step user experience to develop and implement ML techniques. For example, embodiments may include computing a health score for various aspects of developing and/or optimizing ML models, and using the health score, and the factors contributing thereto, to guide production of a valuable ML model. These and other embodiments are described and claimed.

Graphical user interface for automated machine learning model development with data health assessment

Various embodiments are generally directed to techniques for dynamically integrating ML functionality into computing systems, such as a content services platform (CSP), for instance. Many embodiments include ML integrated into a CSP and using production content as corpora (e.g., training and/or evaluation data). Some embodiments are particularly directed to generating and updating data for training and evaluating machine learning (ML) models, then making identified ML models available in various target environments. For example, embodiments may provide automatic, or semi-automatic, updating and deploying of ML models for making inferences, such as inferring labels for data in a content repository of a CSP.

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Brooklyn, NY, United States of America

Gethin Paul James