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
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 and stakeholder groups. Because the requisite investment is one semester-long undergraduate course rather than a year in a graduate program, these tools will likely become a core component of undergraduate programs, and over time, even the high school curriculum.
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
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