Explaining Machine Learning

Zack Labe discusses the use of explainability methods in machine learning and its potential impact on climate science. He shares his experiences with LayerWise relevance propagation and the challenges of interpreting the results. Zack envisions these methods becoming standard in climate science research, allowing for better understanding and communication of machine learning predictions.