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The Springtime Python package helps to streamline workflows for doing machine learning with phenological datasets.

Phenology is the scientific discipline in which we study the lifecycle of plants and animals. A common objective is to develop (Machine Learning) models that can explain or predict the occurrence of phenological events, such as the blooming of plants. Since there is a variety of data sources and existing tools to retrieve and analyse phenology data, it is easy to get lost and disorganized.

With Springtime, we aim to provide a more streamlined workflow for working with a variety of datasets and (ML) models. You can run Springtime as a command line tool in a terminal or use it as a Python library e.g. in a Jupyter notebook.

Example task

Predict the day of first bloom of the common lilac given indirect observations (e.g. satellite data) and/or other indicators (e.g. sunshine and temperature).