A system for storage and analysis of machine learning operations
Author(s)Subramanyam, Harihar G
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
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Data scientists go through an iterative process when building machine learning models. This process includes operations like feature selection, cross validation, model fitting, and evaluation, which are repeated until a sufficiently accurate model is produced. This thesis describes ModelDB Server and the ModelDB Spark Client, which record operations as the data scientist performs them, stores the operations and models in a central database, and exposes an API for gleaning information from the operations and models. ModelDB Server is library agnostic and it can serve as a foundation for other applications. ModelDB Spark Client is a library for the Apache Spark ML machine learning library that lets the data scientist log their operations and models with minimal code changes. ModelDB Server and Spark Client have low time and space overhead for large training dataset sizes and the overhead is independent of the dataset size.
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 111-113).
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.; Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology
Electrical Engineering and Computer Science.