VN1 Forecasting - Accuracy Challenge Phase 1
Share:
Finished
competition-bg

VN1 Forecasting - Accuracy Challenge Phase 1

Flieber, Syrup Tech, and SupChains Launch an AI-Driven Supply Chain Forecasting Competition

VN1 Forecasting - Accuracy Challenge
Machine Learning/AI
Enterprise
E-commerce/Retail
Total Prize 20,000
Scroll To Top

Notebooks

Community contributed notebooks to help you get started right away

9 Notebooks

Unpivotting date columns

For those who prefer to have a proper date column.

Zyad TABAT

3 months ago

Exponential Smoothing models implemented in Pandas

Various exponential smoothing models implemented in pandas

Nicolas Vandeput

3 months ago

NeuralForecast starter

Uses DeepNPTS to generate predictions

Olivier Sprangers

3 months ago

MLForecast starter

Uses LightGBM to generate predictions

Olivier Sprangers

3 months ago

StatsForecast starter

Uses AutoETS to generate predictions

Olivier Sprangers

3 months ago

Univariate forecast using Fable Package in R

This notebook demonstrates univariate time series modeling using the fable package in R. It includes data preparation, exploratory analysis, and the development of multiple forecasting models (sNaive, ARIMA, ETS, Mean, and Drift) with parallel processing, followed by forecast accuracy evaluation.

Harsha Halgamuwe Hewage

3 months ago

Introducing MFLES! Score ~.57

Learn about a new algorithm on the scene and get a good score along the way!

Tyler Blume

2 months ago

Forecasts from ETS/iETS model

This notebook describes how ETS/iETS from the smooth package in R can be used to produce forecasts. The score is 0.613417419243

Ivan Svetunkov

2 months ago

Polars starter

Use Polars expressions with statsforecast to generate predictions

Torben Windler

2 months ago

Join our private community in Discord

Keep up to date by participating in our global community of data scientists and AI enthusiasts. We discuss the latest developments in data science competitions, new techniques for solving complex challenges, AI and machine learning models, and much more!