Charles Martin, an AI and data science consultant, created WeightWatcher, a unique tool for analyzing neural networks without needing test data. In this discussion, he dives into the challenges of evaluating machine learning models, especially in fields like retail and finance. He emphasizes the significance of human judgment and innovative methods for model assessment. Martin also highlights the integration of statistical methods from physics in AI, showcasing how they can enhance model training and optimization processes.
WeightWatcher, created by Charles Martin, is an open source diagnostic tool for analyzing Neural Networks without training or even test data! Charles joins us in this episode to discuss the tool and how it fills certain gaps in current model evaluation workflows. Along the way, we discuss statistical methods from physics and a variety of practical ways to modify your training runs.