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M5 Forecasting Project

This project contains analysis and forecasting models for the M5 Forecasting competition.

Overview

The M5 Forecasting competition involves predicting sales data for Walmart stores across different states. This project uses time series analysis and machine learning techniques to forecast future sales.

Files

  • m5_forecasting.ipynb - Main Jupyter notebook containing data analysis, visualization, and forecasting models

Getting Started

Prerequisites

Make sure you have the following installed:

  • Python 3.8+
  • Jupyter Notebook or JupyterLab

Installation

  1. Clone or download this repository
  2. Install required dependencies: 
    pip install pandas numpy matplotlib seaborn scikit-learn

Usage

  1. Open the notebook: 
    jupyter notebook m5_forecasting.ipynb
  2. Run the cells sequentially to perform analysis and generate forecasts

Data

The M5 dataset includes:

  • Historical sales data
  • Calendar information
  • Product details
  • Store information

Project Structure

The notebook typically includes:

  • Data loading and preprocessing
  • Exploratory Data Analysis (EDA)
  • Feature engineering
  • Model training and evaluation
  • Forecasting and predictions

License

This project is for educational and research purposes.

Acknowledgments

  • M5 Forecasting Competition
  • Kaggle