Machine Learning is a crucial asset for Industrial IoT scenarios but is a complex technology that presents many challenges. This IoT Show will discuss the common Industrial IoT prediction patterns Machine Learning is used to implement and will demo resources and samples made available on GitHub to help you become familiar with Machine Learning for IIoT.
Applying Machine Learning to almost any problem is getting easier every day, but it requires a disciplined approach to evaluate a use case and build repeatable processes to scale these techniques beyond a single use case. In this article we will discuss an approach on how to evaluate use cases faster and build this repeatable process. Operationalizing machine learning projects require continuous experimentation and multiple components, for this article we will focus on aspects to accelerate ML lifecycle for Industrial IoT projects.No-risk testing, You can test changes to products/systems with no risk of permanent damage.
Machine Learning is a major component in most manufacturing transformation projects today. A key skill for a machine learning project is the ability to understand the data coming out of both the IT and OT systems. Most customers do have experts who understand their domains very well, but they lack the skills to apply these new machine learning techniques to better reason about the data. If these domain experts are enabled with the right set of tools and techniques, they can amplify their skills.
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