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Machine Learning at the Edge- When, Why, How?  Part 2 of 3

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Description

The IoT led to an explosion of data. Though it was once thought the cloud would handle this data, the industry soon realized this was impractical. As a result, edge computing has increased in popularity. One of the most fascinating things about edge computing is that it can be accomplished on a wide range of device categories, from MCUs to complex SoCs with high-end A-class cores, GPUs, and ML accelerators.

 

Click here to register.

 

Part 2:

November 15, 10:30 - 11:30 AM CST

- Machine Learning at the Edge

- ML implementation using MCUs with ARM Cortex-M4 and M7

- ML implementation with i.MX application processors

- Vision, Voice and Vibration as ML examples

 

When and Where

  • Start Time:

    Nov 15, 2018 10:30 AM CST (America/Chicago)
  • End Time:

    Nov 15, 2018 11:30 AM CST (America/Chicago)
  • Location:

    https://attendee.gotowebinar.com/register/7275814081879388161?source=E14

Event Info

  • Event Type:

    Webinar
  • Event Visibility & Attendance Policy:

    Open

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