Abstract
Machine Learning emphasizes the computational work of software to process sample and/or historic data with the goal of uncovering interesting patterns, identifying objectives, and predicting outcome. For example, machine learning might uncover that for the past 14 years of worker’s compensation claims data, ear injuries in construction have an 88 percent chance of staying open for 180 days. Or when provided with juvenile offender historic data and recent juvenile crime data, machine learning might predict a 79 percent chance that a given juvenile’s next offense will result in an assault.
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© 2015 Marshall Copeland, Julian Soh, Anthony Puca, Mike Manning, and David Gollob
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Copeland, M., Soh, J., Puca, A., Manning, M., Gollob, D. (2015). Microsof t Azure Machine Learning. In: Microsoft Azure. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-1043-7_14
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DOI: https://doi.org/10.1007/978-1-4842-1043-7_14
Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-1044-4
Online ISBN: 978-1-4842-1043-7
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