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Neural Networks & Teachable Machines – Week 3 at Berkeley

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Manage episode 482394781 series 2864788
Content provided by Ancast Podcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ancast Podcast or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

In Episode 7, Ben explores neural networks and deep learning from Week 3 of his Berkeley ExecEd journey. Joined by co-host HAIley, he unpacks classification vs regression, loss functions, and adversarial inputs — and shares his real-world experiment using Google’s Teachable Machine on his podcast audio archive. The episode highlights how training data, error penalties, and robustness all shape effective AI models in the real world.

  continue reading

48 episodes

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iconShare
 
Manage episode 482394781 series 2864788
Content provided by Ancast Podcast. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ancast Podcast or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://staging.podcastplayer.com/legal.

In Episode 7, Ben explores neural networks and deep learning from Week 3 of his Berkeley ExecEd journey. Joined by co-host HAIley, he unpacks classification vs regression, loss functions, and adversarial inputs — and shares his real-world experiment using Google’s Teachable Machine on his podcast audio archive. The episode highlights how training data, error penalties, and robustness all shape effective AI models in the real world.

  continue reading

48 episodes

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