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Reproducible Data Science in Python | Scipy 2019 Tutorial | Xu Fei, Chandrasekhar Ramakrishnan
Blaze + Odo | SciPy 2015 | Phillip Cloud
Building Python Data Apps with Blaze and Bokeh | SciPy 2015 Tutorial | Christine Doig-Cardet
Kevin Lee - Bring Accelerated Computing to Data Science in Python | SciPy 2025
Python-Powered Machine Learning in the Cloud
A Cloud Service to Record Simulation Metadata | SciPy 2015 | Yannick Congo
The need for serverless Python | SciPy 2021
So How ARE Scientists Using Python on Supercomputers | SciPy 2015 | Michael Milligan
Lightning Talks | SciPy 2015 | 20150710
Characterizing the Seafloor with Python as a Toolbox | SciPy 2015 | Johanna Hansen
Giménez & Lopez - Processing Cloud optimized data in Python with Serverless Functions | SciPy 2025
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Last Updated: September 30, 2026
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... is start introducing some of the Description What do you do if you have a lot of models to fit, don't want to spend all day with your laptop as a space heater, and ... So before you know I started programming in The expectation of reproducibility in scientific work has been long established, and, increasingly, communities and funding ... Guys about Blaze and AO today so let's just jump right in uh so Blaze what is Blaze it's an interface for Okay so what was the al-azhar on the defining the Welcome to the machine learning and Yes certainly um I think there there's a lot of there's a lot of opportunity for doing some some additional
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