Airflow: your ally for automating machine learning and data pipelines
Enrica Pasqua, Bahadir Uyarer
Big Data, Infrastructure, Machine Learning, Data Engineering

Automate your machine learning and data pipelines with Apache Airflow

Are you sure about that?! Uncertainty Quantification in AI
Florian Wilhelm
Artificial Intelligence, Deep Learning, Data Science, Machine Learning, Science

Are you sure about that?! Uncertainty Quantification in AI helps you to decide if you can trust a prediction or rather not.

Beyond Paradigms: a new key to grok Python & other languages
Luciano Ramalho
Algorithms, Code-Review

#BeyondParadigms: Languages like Python and Go don't fit programming paradigm categories very well. A more pragmatic and practical way to understand languages is focusing on features. This is what "Beyond Paradigms" is about.

Docker and Python - A Match made in Heaven
Dr. Hendrik Niemeyer
Big Data, DevOps, Infrastructure

Learn how to build and ship Python software with Docker Containers.

Fairness in decision-making with AI: a practical guide & hands-on tutorial using Aequitas
Pedro Saleiro
Data Science, Machine Learning, Use Cases

In this tutorial, we are going to deep dive into algorithmic fairness, from metrics and definitions to practical case studies, including bias audits using Aequitas (http://github.com/dssg/aequitas) in real policy problems where AI is being used

Gaussian Progress
Vincent Warmerdam
Artificial Intelligence, Algorithms, Data Science, IDEs/ Jupyter, Machine Learning, Statistics

gaussian progress. it's meta, but also the most normal conference title this year!

Tools that help you get your experiments under control
Katharina Rasch
Artificial Intelligence, Data Science, DevOps, Infrastructure

There is now a wealth of tools that support data science best practices (e.g. tracking experiments, versioning data). Let’s take a look at which tools are available and which ones might be right for your project.

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