What is Greykite?
It is a forecast library that allows you to do exploratory data analysis (EDA), forecast pipeline, model tuning, benchmarking, etc. It includes the Silverkite model, a forecast model developed by Linkedin, which allows feature engineering, automatic changepoint detection, holiday effects, various machine learning fitting methods, statitical prediction bands, etc.
Greykite is a tool in the Machine Learning Tools category of a tech stack.
Greykite is an open source tool with 1.7K GitHub stars and 89 GitHub forks. Here’s a link to Greykite's open source repository on GitHub
Who uses Greykite?
- Provides time series regressors to capture trend, seasonality, holidays, changepoints, and autoregression, and lets you add your own
- Fits the forecast using a machine learning model of your choice
- Provides powerful plotting tools to explore seasonality, interactions, changepoints, etc
- Provides model templates (default parameters) that work well based on data characteristics and forecast requirements (e.g. daily long-term forecast)
- Produces interpretable output, with model summary to examine individual regressors, and component plots to visually inspect the combined effect of related regressors
- Facilitates interactive prototyping, grid search, and benchmarking. Grid search is useful for model selection and semi-automatic forecasting of multiple metrics
- Exposes multiple forecast algorithms in the same interface, making it easy to try algorithms from different libraries and compare results
- The same pipeline provides preprocessing, cross-validation, backtest, forecast, and evaluation with any algorithm
Greykite Alternatives & Comparisons
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