Deep Learning Foundations

Josh delves into the theoretical underpinnings of deep learning, emphasizing the importance of proper initialization and parameterization for building robust agents. Insights include the potential elimination of hyperparameter tuning and the parallels between machine learning's current phase and the historical progression of physics.