项目作者: tcdat96
项目描述 :
a short program that analyzes time-series of sales to forecast future demand of certain products from a set of stores
高级语言: Jupyter Notebook
项目地址: git://github.com/tcdat96/product-demand-forecast.git
————————————— Prerequisites ———————————————
- numpy
- pandas
- sklearn
- seaborn
- statsmodels
- tbats
- xgboost
- tqdm
These can be easily installed with pip, something like
pip install -U numpy pandas sklearn seaborn statsmodels tbats xgboost tqdm
or if you already have the common ones
pip install -U tbats xgboost tqdm
————————————— File Structure ——————————————-
- All the code is written in demand-forecast.ipynb
- A python script demand-forecast.py is also included if you want to run it with command
- The folder ‘backup’ saves all prediction, so we don’t need to rerun it every time.
If you want to rerun any part, simply delete the corresponding saved file.