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Frictionless Data for Reproducible Biology |SciPy 2020| Lilly Winfree
Day 2 SciPy Tools Plenary Session | SciPy 2019 |
Andreas Schreiber - Reproducible Science with Python
Reproducible Data Science with Machine Learning
Complexity Science | Scipy 2019 Tutorial | Allen Downey
RAPIDS: Open GPU Data Science | Scipy 2019 Tutorial | Scopatz, Becker, Kraus, Gama Dessavre
Optimizing Python Based Spectroscopic Data Processing on NERSC Supercomputers | SciPy 2019 |
Karthik Ram | A guide to modern reproducible data science with R | RStudio (2019)
Raoul-Gabriel Urma: Advanced Software Testing for Data Scientists | PyData New York 2019
Reproducible data dependencies for Jupyter - Jackson Brown, Aneesh Karve
PyDDA: A New Pythonic Package for Wind Retrievals | SciPy 2019 | Robert Jackson
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Last Updated: October 26, 2026
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Bio: Didrik is an expert in artificial intelligence, Jodie Burchell 2016.pycon-au.org/schedule/127/view_talk You've seen a great idea on someone's blog that you think ... Being able to explain your own code a few months after you wrote it is hard. Imagine having to explain the decisions of some AI ... The RAPIDS suite of open source software libraries gives you the freedom to execute end-to-end This talk is a case study that describes how a Resources: github.com/karthik/rstudio2019. The journey to deploy a model to production starts with testing it rigorously, including its code implementation. In this PyDDA is a new community framework aimed at wind retrievals that depends only upon utilities in the
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