Hierarchical Forecasting in Python - Introduction to the Hierarchical Forecast Library
Data Council via YouTube
Overview
Explore hierarchical forecasting techniques in Python through this 25-minute conference talk by Max Mergenthaler, CEO and Co-Founder of Nixtla. Delve into the open-source Hierarchical Forecast library, which offers reconciliation algorithms, preprocessed datasets, evaluation metrics, and statistical baseline models. Learn how this Python-based framework bridges the gap between statistical modeling and Machine Learning in time series analysis. Gain insights from Mergenthaler's decade of experience in the ML industry and his contributions to forecasting algorithms and decision theory. Discover how to effectively handle time series datasets organized into structures with different levels or hierarchies of aggregation, enhancing your ability to make accurate predictions and informed decisions in data-driven environments.
Syllabus
Hierarchical Forecasting in Python | Nixtla
Taught by
Data Council