The Modeltime R package & #Forecasting Framework can now forecast multiple #TimeSeries Groups at once using #MachineLearning Models. We showcase use of Modeltime on the Walmart Sales Demand Data Set (7-Time Series Groups). Here's the Table of Contents 👇
TABLE OF CONTENTS
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- "Nostradamus" Auto-Forecast Shiny App Demo - 0:0:35
- Agenda - 8:11
- Modeltime Ecosystem - 9:34
- Modeltime - 9:34
- Modeltime Ensemble - 13:12
- Modeltime Resample - 15:23
- Roadmap for Modeltime - 17:14
- COMING SOON: Modeltime GluonTS - 17:14
- 45-Minute Code Demo - Forecasting at Scale w/ Modeltime - 21:53
- Overview & Project Setup - 21:53
- 1.0 Libraries - 23:40
- 2.0 Data - Walmart Sales Demand - 24:73
- 3.0 Time Series Data Preparation & Forecast Horizon - 25:50
- 4.0 Splitting Train/Test - 31:23
- 5.0 Preprocessor (Feature Engineering) - 33:08
- 6.0 Machine Learning (5 Models - XGBoost, SVM, Random Forest, Prophet, Prophet Boost) - 36:23
- 7.0 Modeltime Workflow - 39:43
- 8.0 Ensemble - 44:45
- 9.0 Conclusion & Time Series Course - 49:24
- BONUS APP [LL PRO MEMBERS] - Nostradamus Lite - 51:02
- Your Transformation - How To Learn Modeltime + Shiny - 52:20
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- Q&A - 1:04:48
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Негізгі бет Forecasting Multiple Time Series with Modeltime | Bonus Auto-Forecast Shiny App [Lab 46]
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