ASUG Blog

Underfit vs. Overfit: Why Your Machine Learning Model May Be Wrong
Paul Kurchina
Paul Kurchina in Digital Transformation, Machine Learning January 25, 2018

Underfit vs. Overfit: Why Your Machine Learning Model May Be Wrong

Just shy of 60 years old, machine learning has never looked so good. Exponential data growth, advanced algorithms, and powerful computer processing are enabling the technology to fulfill its ultimate destiny: Identifying profitable opportunities and avoiding unknown risks by evaluating massive volumes of complex data and delivering accurate results in real time.

However, during the Americas’ SAP Users’ Group (ASUG) webcast, “Guide to the Machine Learning Galaxy: How Your ERP Knowledge Enables Value-Driven Intelligent Processes,” Darwin Deano,..

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