tuesday-13:10 Session List
Battle of Pipelines - who will win python orchestration in 2022?
Jannis Grönberg
Architecture, Data Engineering, DevOpsYou struggle choosing the right #orchestration tool in #Python ? Join this #PyCon talk about when it's best to use #Kubeflow, #Airflow or #Prefect and learn how to automate your #data #pipelines and #ML workflows. #DataScience #dataengineering #DevOps #MLOps
Detecting drift: how to evaluate and explore data drift in machine learning systems
Emeli Dral
Best Practice, Data Visualization, StatisticsWhen ML model is in production, you might encounter data and prediction drift. How exactly to detect and evaluate it? I'll share in this talk.
Forget ‘web 3.0’, let's talk about ‘web 0.0’. A brief history of the Internet, and the World Wide Web.
Dom Weldon
Art, Social Sciences, TheoryForget ‘web 3.0’, let's talk about ‘web 0.0’. A brief history of the Internet, and the World Wide Web.
Overcoming 5 Hurdles to Using Jupyter Notebooks for Data Science, by the JetBrains Datalore Team
Alena Guzharina
Data Visualization, Jupyter, ReproducibilityOvercoming 5 Hurdles to Using Jupyter Notebooks for Data Science, by the JetBrains @Datalore Team Join our talk to discuss setting up environments, working with data, writing code without IDE support, and sharing results, as well as collaboration and reproducibility.
What are data unit tests and why we need them
Theodore Meynard
Best Practice, Data EngineeringThis talk will introduce the concept of data unit tests and why they are important in the workflow of data scientists when building data products.
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