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.
