Machine Learning and the IoT are a match made in heaven. After all, IoT devices collect mountains of sensor data, what better way to uncover insights and actions than through sophisticated, modern computing methods like ML and AI? The problem is, leveraging ML with IoT has historically meant backhauling all your sensor data to the Cloud. When the cloud is involved, security is a concern, and in the realm of IoT, security is often a dirty word.
But modern embedded systems, microcontrollers and single-board computers are getting more powerful, and more sophisticated, and its becoming increasingly possible to bring Machine Learning closer to sensors and IoT devices. "Edge ML" enables quicker insights, tighter security, and even true predictive action, and it's going to become the norm in the IoT in the near future.
In this session, we'll explore the state of the art in ML, work through the process of building and training models in the cloud, and finally, explore building IoT solutions that can run ML inferencing in real-time on low-cost devices.
What you'll learn