Optimizing ML/AI Workflows with Essential Airflow Features

With recent advancements in generative AI, teams are being tasked to quickly implement ML/AI initiatives. Luckily, Airflow is here to help by enabling you to create dynamic, scalable, and robust ML/AI pipelines.

Join Kenten Danas, Manager, Developer Relations, at Astronomer, and Tamara Fingerlin, Developer Advocate, at Astronomer for this webinar that will cover best practices for using the latest Airflow features for generative AI and machine learning use cases:

Create dynamic, scalable, and robust ML/AI pipelines in Airflow
Connect traditional and ML/AI DAGs
Utilize key Airflow features for Day 2 ML/AI operations
And more!

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Apache Airflow already is the standard for data orchestration and the backbone of any modern data-driven organization. With recent leaps in generative AI, more and more teams are asked to implement cutting edge generative AI use cases in a fast-changing ecosystem of tools and techniques.

Luckily, Airflow is here to help you take your machine learning and AI journey to the next level! In 2023, 28% of Airflow users were already using Airflow for machine learning use cases, leveraging recent Airflow features to create dynamic, scalable and robust ML&AI pipelines.

In this webinar, we cover best practices for using the latest Airflow 2.9 features for generative AI and general machine learning use cases.