https://github.com/desininja/facebookprophet

Predicting the future prices of Avocado using Facebook prophet
https://github.com/desininja/facebookprophet

Last synced: 3 months ago
JSON representation

Predicting the future prices of Avocado using Facebook prophet

• Host: GitHub
• URL: https://github.com/desininja/facebookprophet
• Owner: desininja
• Created: 2020-11-22T18:02:33.000Z (almost 5 years ago)
• Default Branch: main
• Last Pushed: 2020-11-22T18:29:13.000Z (almost 5 years ago)
• Last Synced: 2025-01-02T21:17:05.548Z (10 months ago)
• Language: Jupyter Notebook
• Size: 2.5 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
# facebookprophet

Predicting the future prices of Avocado using Facebook prophet.

Prophet is an open source tool used for time series forecasting.

- You must install fbprophet package as follows: 

     pip install fbprophet

- If you encounter an error, try: 

    conda install -c conda-forge fbprophet

    

    

## Understanding the intuition behind facebook prophet:

- Prophet is an open source software released by Facebook's core Data Science team.

- Prophet is a procedure for forecasting time series data based on an additive model where non-linear treends are fit with yearly, weekly, and daily seasonality, plus holiday effects.

- Prophet works best with time series that have strong seasonal effects and several seasons of historical data.

- For more information, please check this out:

    - https://www.analyticsvidhya.com/blog/2018/05/generate-accurate-forecasts-facebook-prophet-python-r/

    - https://facebook.github.io/prophet/docs/quick_start

- Prophet implements an additive regression model with four elements:

    - A piecewise linear, Prophet automatically picks up change points in the data and identifies any change in trnds.

    - A yearly seasonal component modeled using Fourier series.

    - A weekly seasonal component.

    - A holiday list that can be manually provided.

# Facebook Prophet Features

* Accurate and Fast

  - Facebook teams uses Prophet for accurate forecasting and planning.

  - Prophet can generate results in seconds.

* Automatic

  - No need to perform data preprocessing.

  - Prophet works with missing data with several outliers.

* Domain knowledge integration

  - users can tweakforecast by manually adding domain specific knowledge.

  

### A few model specification during training:

The data should consist of only two columns one date column named as "ds" and other the target column named as "y".