Building AI Models for High-Frequency Streaming Data – Part Two - KDnuggets

AI continues making headlines in the data science community, and predictive models are front and center in engineering applications such as autonomous driving and equipment monitoring. Introducing AI models into engineering systems can be challenging, however, especially when predictions must be reported in near real-time on data from multiple sensors. Many data scientists have implemented machine or deep learning algorithms on static data or in batch, but what considerations must you make when building models for a streaming environment? In this post, we will discuss these considerations. If streaming movies or music comes to mind, you've got the right idea! Data is incoming continuously, but instead of simply watching, actions must be taken based on the information.