IoT machine learning has revolutionized the way businesses operate, by transforming vast amounts of data into actionable insights and decision-making tools. The era of technology is constantly evolving, with new advancements appearing almost every day. One such field that has gained immense popularity in recent times is the combination of Internet of Things (IoT) and Machine Learning (ML). This innovative blend of technologies is opening doors to new business opportunities, and is poised to play a major role in shaping the future of our world. In a world that is becoming increasingly data-driven, IoT machine learning provides a new and exciting avenue for businesses to leverage the power of big data, and gain a competitive edge in the market.

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.