/m5-competition

M5 competition project (for practice)

Primary LanguageJupyter Notebook

M5 Modelling

Background

Please look at the Kaggle competition for background! There is the Accuracy Competition and the Companion Competition for uncertainty.

Please also check out the Competitor's Guide.

This repository also tries to estimate elasticities and other effect sizes, rather than just focusing on accuracy.

Setup

  1. Create a conda environment called m5-comp:

    conda env create

  2. Then, install the library in editable mode:

    pip install -e .

  3. Set up your Kaggle API credentials, as outlined here.

  4. Download and unzip the data:

    kaggle competitions download -c m5-forecasting-accuracy -p data

unzip data/m5-forecasting-accuracy.zip -d data

  5. Run jupyter.

Runnin in Julia

  1. Install Julia.

  2. Activate the conda env, then run the following to install the required Julia packages:

    ]activate .
instantiate

    Backspace to exit package mode, then install the IJulia (Jupyter) kernel:

    using IJulia
installkernel("julia4threads", env=Dict("JULIA_NUM_THREADS"=>"4", "JULIA_PROJECT"=>pwd()))

  3. Run jupyter notebook and select the kernel you want (either default or 4-thread kernel).