Introduction to Embedded Machine Learning 3.3.3 - Sensor Fusion

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Embedded machine learning is the process of running machine learning algorithms (including deep learning) on embedded systems, such as microcontrollers and single board computers. These videos come from the Coursera course: Introduction to Embedded Machine Learning. If you would like to take the full course, complete projects, and earn a certificate in embedded machine learning, please go here:

In this video, Shawn provides examples of sensor fusion, where 2 or more (similar or different) sensors can be combined to gain additional understanding of the environment. While sensor fusion is traditionally accomplished using deterministic techniques (e.g. Kalman filter), we can sometimes use machine learning to accomplish similar tasks.
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