This project contains analysis and forecasting models for the M5 Forecasting competition.
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.
m5_forecasting.ipynb- Main Jupyter notebook containing data analysis, visualization, and forecasting models
Make sure you have the following installed:
- Python 3.8+
- Jupyter Notebook or JupyterLab
- Clone or download this repository
- Install required dependencies:
pip install pandas numpy matplotlib seaborn scikit-learn
- Open the notebook:
jupyter notebook m5_forecasting.ipynb
- Run the cells sequentially to perform analysis and generate forecasts
The M5 dataset includes:
- Historical sales data
- Calendar information
- Product details
- Store information
The notebook typically includes:
- Data loading and preprocessing
- Exploratory Data Analysis (EDA)
- Feature engineering
- Model training and evaluation
- Forecasting and predictions
This project is for educational and research purposes.
- M5 Forecasting Competition
- Kaggle