Adobe, Inc.

Ashok Pancily Poothiyot

Vidit Bhatia

Nirmal Mani

Matthew Colon

Sathya Arun

Methods and systems are provided for evaluating providing insight into complex machine learning models to facilitate optimization of the models at scale. In particular, a system can guide and/or implement model training and evaluation in various machine learning environments. Further, the system is capable of using standardized evaluation metrics to provide insight into the success of iterations of a machine learning model. Additionally, the system allows for presenting visualizations based on such evaluation metrics to facilitate gaining insight into one or more machine learning models and/or instances of a machine learning model.

Model insights framework for providing insight based on model evaluations to optimize machine learning models

The present disclosure relates to systems, methods, and non-transitory computer-readable media for utilizing a parameterized notebook to adaptively generate visualizations regarding machine-learning models. In particular, the disclosed systems can generate a parameterized notebook based on a user-defined visualization recipe and provide parameter values that correspond to the machine-learning model to the parameterized notebook. Upon execution of the user-defined visualization recipe via the parameterized notebook, the disclosed systems can extract visualization data corresponding to the machine-learning model from the parameterized notebook. In addition, the disclosed systems can generate visualizations based on the visualization data and provide the generated visualizations for display in a graphical user interface.

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San Jose, CA, United States of America

Ashok Pancily Poothiyot