Jump to ContentJump to Main Navigation
Automated Machine Learning for Business - Oxford Scholarship Online
Users without a subscription are not able to see the full content.

Automated Machine Learning for Business

Kai R. Larsen and Daniel S. Becker

Abstract

In Automated Machine Learning for Business, we teach the machine learning process using a new development in data science: automated machine learning. AutoML, when implemented properly, makes machine learning accessible to most people because it removes the need for years of experience in the most arcane aspects of data science, such as the math, statistics, and computer science skills required to become a top contender in traditional machine learning. Anyone trained in the use of AutoML can use it to test their ideas and support the quality of those ideas during presentations to management an ... More

Keywords: automated machine learning, time-aware analytics, time-series analytics, confusion matrix, DataRobot, driverless AI, artificial intelligence, confusion matrix, supervised machine learning

Bibliographic Information

Print publication date: 2021 Print ISBN-13: 9780190941659
Published to Oxford Scholarship Online: July 2021 DOI:10.1093/oso/9780190941659.001.0001

Authors

Affiliations are at time of print publication.

Kai R. Larsen, author
Associate Professor of Information Systems, Leeds School of Business, University of Colorado Boulder

Daniel S. Becker, author
Data Scientist, Google