The Prophet library is an open source library designed to make predictions for univariate time series datasets. It is easy to use and by default is designed to automatically find a good set of hyperparameters for the model to make predictions for data with trends and seasonality.
You can access presentations and notebooks in the repo.
Also you can access dozens of different datasets with this link
To run this project you need the following libraries:
fbprophet
pandas
matplotlib
plotly
scikit-learn
Machine Learning Mastery Simple time series training with Facebook Prophet. Source
- https://github.com/kedarvkunte/End-to-End-Data-Science-Project-Time-Series-Analysis-for-Temperature-Forecasting-using-ARIMA-Model
- https://towardsdatascience.com/an-end-to-end-project-on-time-series-analysis-and-forecasting-with-python-4835e6bf050b
- https://www.machinelearningplus.com/time-series/time-series-analysis-python/
- https://medium.com/analytics-vidhya/time-series-analysis-a-quick-tour-of-fbprophet-cbbfbffdf9d8
- https://towardsdatascience.com/a-quick-start-of-time-series-forecasting-with-a-practical-example-using-fb-prophet-31c4447a2274
- https://machinelearningmastery.com/time-series-forecasting-with-prophet-in-python/
- https://scribe.rip/analytics-vidhya/facebook-prophet-algorithm-in-time-series-analysis-90da4a7c1b16
- https://www.youtube.com/watch?v=KvLG1uTC-KU&ab_channel=NicholasRenotte
- https://www.analyticsvidhya.com/blog/2020/10/time-series-forecasting-using-facebook-prophet-library-in-python/
- https://medium.com/swlh/time-series-analysis-7006ea1c3326
- https://medium.com/featurepreneur/a-roadmap-for-time-series-analysis-3faf49b2126
- https://towardsdatascience.com/the-complete-guide-to-time-series-analysis-and-forecasting-70d476bfe775