3 machine learning best practices to use in IoT projects

In an ideal world, organizations could easily plan machine learning for IoT with the right technical experts, and components would perfectly integrate with each other. Unfortunately, no matter how well a team researches IoT machine learning before it starts development, some of their assumptions will be proven wrong and they will face unexpected challenges. During her IoT Tech Expo 2020 presentation, "Building Machine Learning Products -- a Best Practice Approach," Jenn Gamble, data science practice lead at Very, identified the required skills to implement machine learning with IoT and how teams can adopt best practices, approach software development and handle unexpected difficulties. "A lot of the data science development lifecycle is actually very different than what the Agile software development lifecycle is. A lot of those hard-won best practices from software engineering, the data science community was not always aware of, or, at least, not fully embracing or benefiting from," Gamble said.