2026-09-19T01:44:36Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1197052026-06-06T00:55:05Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Sam Madden.
Tromba, Isabella M
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2018-12-18T19:46:33Z
2018-12-18T19:46:33Z
2018
2018
http://hdl.handle.net/1721.1/119705
1078154256
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.
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 61-64).
MakeML is a software system that enables knowledge workers with no programming experience to easily and quickly create machine learning models that have competitive performance with models hand-built by trained data scientists. MakeML consists of a web-based application similar to a spreadsheet in which users select features and choose a target column to predict. MakeML then automates the process of feature engineering, model selection, training, and hyperparameter optimization. After training, the user can evaluate the performance of the model and can make predictions on new data using the web interface. We show that a model generated automatically using MakeML is able to achieve accuracy better than 90% of submissions for the Titanic problem on the public data science platform Kaggle.
by Isabella M. Tromba.
M.Eng.
64 pages
eng
Massachusetts Institute of Technology
MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
MakeML : automated machine learning from data to predictions
Automated machine learning from data to predictions
Thesis
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Publication
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<Abstract>MakeML is a software system that enables knowledge workers with no programming experience to easily and quickly create machine learning models that have competitive performance with models hand-built by trained data scientists. MakeML consists of a web-based application similar to a spreadsheet in which users select features and choose a target column to predict. MakeML then automates the process of feature engineering, model selection, training, and hyperparameter optimization. After training, the user can evaluate the performance of the model and can make predictions on new data using the web interface. We show that a model generated automatically using MakeML is able to achieve accuracy better than 90% of submissions for the Titanic problem on the public data science platform Kaggle.</Abstract>
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