Juan Castillo del Río: Quantifying Uncertainty @ PyCon Ireland 2024 скачать в хорошем качестве

Juan Castillo del Río: Quantifying Uncertainty @ PyCon Ireland 2024

Quantifying uncertainty with stochastic and machine learning models - Juan Castillo del Río Room 2 Session 11 Uncertainty estimation is a game-changer in banking, trading, retail, and many other fields. The potential applications are endless, and new innovations are emerging across all sectors. Two great examples of uncertainty estimation models are: Financial risk models, which have been helping banks and trading firms navigate market volatility for years, preventing potential bankruptcies. Demand forecasting models, which give valuable insights that allow companies to make better decisions, boosting their efficiency. The best way to understand uncertainty estimation models is by seeing them in action. That’s why in this talk we will walk through some real-world risk estimation examples using Python. We’ll explore the pros and cons of various stochastic and machine learning models currently employed by leading companies. While there is no one-size-fits-all model for quantifying uncertainty, this conference will provide you with useful information to choose the best model for your specific use case.