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A flexible, intuitive and fast forecasting library (By LinkedIn)
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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 GitHub stars and GitHub forks. Here’s a link to Greykite's open source repository on GitHub

Greykite Integrations

Greykite's Features

  • 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

What are some alternatives to Greykite?
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PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
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scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
A parallel computing platform and application programming interface model,it enables developers to speed up compute-intensive applications by harnessing the power of GPUs for the parallelizable part of the computation.
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