Statistics and Applied Mathematics

Project Jupyter

Project Jupyter is a community of open-source developers, scientists, educators, and data scientists. Its goal is to build open-source tools and create community that facilitates scientific research, reproducible and open workflows, education, computational narratives, and data analytics. Jupyter supports over 100 programming languages, and connects data analytics tools across a range of disciplines and communities.

There are several core projects of Jupyter that the Berkeley Institute for Data Science supports:

scikit-image

Scikit-image is a community-driven Python project, consisting of a vast collection of high-quality, peer-reviewed image processing algorithms that are made available to a global community of researchers free of charge and free of restriction. The library is widely used in many different fields, including astronomy, biomedical imaging, and environmental resource management. Scikit-image was founded by BIDS Research Data Scientist Stéfan van der Walt in 2009.

Cesium ML

Cesium-ML is an end-to-end machine learning platform for time-series, that computes machine learning features, builds models, and does prediction. Cesium has two main components—a Python library, and a web application platform that allows interactive exploration of machine learning pipelines. The Cesium library is specifically designed to handle irregularly sampled time series, as is common in astronomy.

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