Pytorch for Forecasting

Sean explains the choice of Pytorch over Tensorflow for forecasting models, emphasizing the need for differentiable models to optimize policy variables. The focus is on creating forecasts with causal effects baked in, allowing for efficient optimization of plans based on the forecasted outcomes.