The AI Frontier in Time-Series Forecasting: Implications for business

This webinar stars Jacomo Carbo, Chief Science Officer at QuantumBlack and Nicolas Chapados, Chief Science Officer at Element AI. They discuss the technical and business gains in time-series forecasting and provide insights into tackling the challenges that lie ahead. Time-series forecasting analyzes past data to predict what might happen in the future. It is central to just about every industry, and for good reason: sometimes even a tiny improvement in accuracy (eg, better prediction of inventory turnover, budget needs, consumer trends) can translate into millions of dollars of operational savings or revenue generation. Until recently, pure machine learning models for time-series forecasting produced underwhelming results, but advances in other areas, such as transfer learning and generalization, have changed the game.