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1、2024 Databricks Inc.All rights reservedMany Model Many Model Forecasting Forecasting in Realin Real-TimeTimeAnastasia ProkaievaAnastasia Prokaieva13 May 202413 May 202412024 Databricks Inc.All rights reserved2024 Databricks Inc.All rights reservedAnastasia Prokaieva Anastasia Prokaieva-Specialist Ar
2、chitect-AI and GeoSpatial-Databricks since 2021,Global SME on AI and product champion on Model Serving-Background in Physics&Applied Mathematics-Book co-Author-“Databricks ML in Action”“Databricks ML in Action”by PacktMeet your SpeakerMeet your Speaker2Lets connect!Lets connect!22024 Databricks Inc.
3、All rights reservedProblem StatementTime Series Forecasting3tz(t)x1(t)x2(t)x3(t)2024 Databricks Inc.All rights reserved2024 Databricks Inc.All rights reservedTypes of Forecasting Algorithms4Predicting individual time series separately.Each model is trained and applied to a specific time series,makin
4、g it suitable for forecasting at a granular level,such as product-level sales forecasting in a large enterprise.Local ModelsGlobal ModelsLocal ModelsGlobal ModelsConsider multiple time series collectively.They forecast across a broader set of data.Global models are useful for capturing complex depen
5、dencies between different time series,making them valuable for broader,cross-entity forecasting tasks.4f()=f()=f()Takes only one time series at a timef()=Learns parameters for multiple time series2024 Databricks Inc.All rights reserved2024 Databricks Inc.All rights reservedTypes of Forecasting Algor
6、ithms5Predicting individual time series separately.Each model is trained and applied to a specific time series,making it suitable for forecasting at a granular level,such as product-level sales forecasting in a large enterprise.Local ModelsGlobal ModelsLocal ModelsGlobal ModelsConsider multiple time