Adobe, Inc.

Nirmal Mani

Shankar Srinivasan

Pari Sawant

Ashok Pancily Poothiyot

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

Systems and methods for developing enterprise machine learning (ML) models within a notebook application are described. The system may include a notebook application, a packaging service, and an online ML platform. The method may include initiating a runtime environment within the notebook application, creating a plurality of files based on a notebook recipe template, generating a prototype model within the data science notebook application by accessing the plurality of files through the runtime environment, generating a production recipe including the runtime environment and the plurality of files, and publishing the production recipe to the online ML platform.

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Sunnyvale, CA, United States of America

Nirmal Mani