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
创建时间: 2020-11-24T20:18:54Z
项目社区:https://github.com/tcdat96/product-demand-forecast

开源协议:

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————————————— Prerequisites ———————————————

  1. numpy
  2. pandas
  3. sklearn
  4. seaborn
  5. statsmodels
  6. tbats
  7. xgboost
  8. 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 ——————————————-

  1. All the code is written in demand-forecast.ipynb
  2. A python script demand-forecast.py is also included if you want to run it with command
  3. 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.