Neural Networks & Teachable Machines – Week 3 at Berkeley episode artwork

EPISODE · May 13, 2025 · 10 MIN

Neural Networks & Teachable Machines – Week 3 at Berkeley

from Broadcast Media: The Inside Track · host Ancast Podcast

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.

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.

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Neural Networks & Teachable Machines – Week 3 at Berkeley

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This episode was published on May 13, 2025.

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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...

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