Hierarchical Time Series Forecasting | Intermittent Demand (M5 Comp)

📖 Learning Labs PRO (get code & #shiny app): https://university.business-science.i...

😀 ABOUT: In Learning Labs PRO Episode 50, Matt tackles an in-depth tutorial on Hierarchical Forecasting using the M5 #Forecasting Competition.

This is a challenging forecasting problem that includes intermittent demand, when demand becomes very granular with lots of zeros. This is also a hierarchical dataset, where there are 50 lower-level time series that are aggregated by the organization's departments and product types.

We'll use #Modeltime along with #Tidymodels and XGBoost, LightGBM, and CatBoost Machine Learning Algorithms.

📋 INTRODUCTION:
Agenda - M5 Forecasting Competition | Tidymodels, Treesnip, Modeltime | XGBoost, LightGBM, CatBoost - 00:00
Introducing the Shiny Hierarchical Forecaster App - 3:46
Business Problem - What is Hierarchical Demand Forecasting & Why Do I Care? - 7:38
Why Learn Tidymodels? 11:00

📖 FULL CODE TUTORIAL
Project Setup - 11:55
Part 1 - XGBoost vs LightGBM vs CatBoost - 14:00
LightGBM Basic Usage (without Tidymodels ☹️) - 15:31
Classification: XGBoost, LightGBM, & CatBoost (with Tidymodels😎) - Agaricus - 17:37
Regression CV: XGBoost, LightGBM, & CatBoost (with Tidymodels😎) - Diamonds - 22:59
Part 2 - FULL HIERARCHICAL FORECASTING TUTORIAL - 25:46
Load the Data, Reshape & Join - 27:19
Quick EDA: Skim Data & Visualize Sales Trends for 6 Product Items - 30:51
FEATURE ENGINEERING: Making the "Full Dataset" - 33:30
Discussion: Hierarchical Forecasting Strategies & Alternatives - 40:01
Splitting Full Data - Data Prepared / Future Data - 44:55
Time Splitting - Train/Test Sets - 46:03
Preprocessing Pipeline (Time Series Features & One-Hot Features) - 46:58
MACHINE LEARNING - 49:37
MODELTIME - Model Comparison & Selection - 53:21
ENSEMBLE LEARNING - Combine Your Best Models into a Super Model - 1:03:12
CONCLUSIONS - 380 Lines of Code for a High-Performance Forecast is GOOD, but can IMPROVE - 1:07:01
LLPRO BONUS - Shiny App Code - Hierarchical Forecaster - 1:09:30

🧙‍♂️ LEARNING RECOMMENDATIONS
How do I learn what Matt just taught? - 1:11:30
👉Is Learning Labs PRO for me? - 1:13:00 - https://university.business-science.i....
What if I'm just starting & learning R shiny much deeper? - 1:14:20
Is the R-Track right for me? - 1:15:00
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