Salesforce Com, Inc.

Amplitude

Mustafa Paksoy

Eric Pollmann

Muhammad Bilal Mahmood

Jeffrey M Bergan

Cynthia Rogers

William Robert Pentney

Kanishka Maheshwari

Zachery Abe Miranda

Implementations described herein relate to methods, systems, and computer-readable media for automated generation and use of a machine learning (ML) model to provide recommendations. In some implementations, a method includes receiving a recommendation specification that includes a content type and an outcome identifier, and determining model parameters for a ML model based on the recommendation specification. The method further includes generating a historical user feature matrix (FM), generating a historical content feature matrix (FM), and transforming the historical user FM and the historical content FM into a suitable format for the ML model. The method further includes obtaining a target dataset that includes historical results for the outcome identifier for a plurality of pairs of user identifiers and content items of the content type. The method further includes training the ML model using supervised learning to generate a ranked list of content items for each user identifier.

Automated machine learning to generate recommendations for websites or applications

An index to be backed up in a computing environment is identified. A staged copy of the index to be backed up is created. The staged copy of the index is segmented. The segments are uploaded to a pre-selected location.

Methods and systems for backing up a search index

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San Francisco, CA, United States of America

Mustafa Paksoy