Which Machine Learning Strategies should you use within your manufacturing AI?
“3 Types of Machine Learning for the Enterprise”
Published 29 January, 2020
By Gartner Analyst Saniye Alaybeyi, Alexander Linden, and Pieter den Hamer
According to research, “Machine learning solves problems by using statistical models that can extract knowledge and patterns from data.”
Many manufacturers are already embracing Machine Learning strategies or intend to do so in the coming months. This report from Gartner covers some of the types of Machine Learning that you can expect to see and when to apply each use case.
In this research, we believe you’ll learn:
- differences between supervised, unsupervised, and reinforcement learning strategies
- how to effectively employ each of these Machine Learning types, and recognize which types of Machine Learning align with your use cases
- why labelling data is important (when available)
- strategies to build upon unsupervised Machine Learning to scale your use cases
Tell us about yourself to read this free report:
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4 Use Cases for Machine Learning
Continuing to find new ways to improve operations requires increased creativity, capacity, and access to critical data. Industrials use Machine Learning to identify opportunities to improve OEE at any phase of the manufacturing process. Learn how to use Machine Learning to solve some of the biggest challenges faced by manufacturers.