Building Machine Learning Pipelines in Airflow with Jupyter Notebooks

Learn how to develop end-to-end machine learning pipelines using Jupyter Notebooks and Airflow in this 38-minute conference talk from the Toronto Machine Learning Series. Discover a pattern for implementing each component of the pipeline in a notebook, parameterizing it with Papermill, and then scaling and scheduling the entire process using Airflow. Gain insights from experienced data scientists Palermo Penano and Kenneth Lau as they share their expertise in building maintainable and scalable machine learning solutions for financial services applications.

Building Machine Learning Pipelines in Airflow with Jupyter Notebooks