With the IoT market set to triple in size by 2020, and massive increases in computing power on small devices, the intersection of IoT and machine learning is a trend that all developers should pay attention to. This talk will cover three core use cases, including: how to manage sourcing data from IoT devices to drive machine-learned models; how to deploy and use trained models on mobile devices; and how to do on-device training with a Raspberry Pi computer.

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#io18 event: Google I/O 2018; re_ty: Publish; product: Cloud - Internet of Things (IoT) - IoT Core, Cloud - Data Analytics - PubSub, Cloud - Containers - Google Kubernetes Engine (GKE), TensorFlow - General, Cloud - AI and Machine Learning - AI Platform; fullname: Laurence Moroney, Kaz Sato; event: Google I/O 2018;