Today we kick off PyDataSci with Luciano Resende, an Open Source AI Platform Architect at IBM and part of the Center for Open Source Data and AI Technology.
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Luciano and I caught up to discuss his work on Jupyter Enterprise Gateway, a scalable way to share Jupyter notebooks and other resources in an enterprise environment. In our conversation, we discuss some of the challenges that arise using Jupyter Notebooks at scale, the role of open source projects like Jupyter Hub and Enterprise Gateway, and some potential reasons for investing in and building custom notebooks. We also explore some common requests from the community, such as tighter integration with git repositories, as well as the python-centricity of the vast Jupyter ecosystem.
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Thanks to our Sponsor!
I’d like to send a huge thanks to our sponsor for this series, IBM. IBM has a long history of engaging in and supporting open source projects that are important to enterprise data science — projects like Hadoop, Spark, Jupyter, Kubernetes, and Kubeflow.
IBM also hosts the IBM Data Science Community, which is a place for enterprise data scientists looking to learn, share, and engage with their peers and industry renowned practitioners. There you’ll find informative tutorials and case studies, Q&As with leaders in the field, and a lively forum covering a variety of topics of interest to beginning and experienced data scientists.
Visit the IBM Data Science Community at ibm.com/community/datascience.
From the Interview
- Center for Open Source Data and AI Technology (CODAIT)
- Jupyter Enterprise Gateway
- Presentation: Strata – Scaling Jupyter with Jupyter Enterprise Gateway
- Bighead: Airbnb’s Machine Learning Platform with Atul Kale
- Supporting TensorFlow at Airbnb with Alfredo Luque
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“More On That Later” by Lee Rosevere licensed under CC By 4.0