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Machine learning for enterprises: Applications, algorithm selection, and challenges
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DOI：10.1016/j.bushor.2019.10.005.png)
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Abstract
En 中文
Machine learning holds great promise for lowering product and service costs, speeding up business processes, and serving customers better. It is recognized as one of the most important application areas in this era of unprecedented technological development, and its adoption is gaining momentum across almost all industries. In view of this, we offer a brief discussion of categories of machine learning and then present three types of machine-learning usage at enterprises. We then discuss the trade-off between the accuracy and interpretability of machine-learning algorithms, a crucial consideration in selecting the right algorithm for the task at hand. We next outline three cases of machine-learning development in financial services. Finally, we discuss challenges all managers must confront in deploying machine-learning applications. (C) 2019 Kelley School of Business, Indiana University. Published by Elsevier Inc. All rights reserved.
Keywords:
Machine learning
Artificial intelligence
Deep learning
Big data
Neural networks
Chatbot
Innovation capability
Resources and capabilities
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