Hi Beam community! We are happy to announce the release of new resources for AI/ML workflows in Apache Beam [1].
A number of community members have been working on a series of documentation guides and end-to-end examples to showcase various common patterns to perform ML tasks with Apache Beam. These patterns include data preprocessing with Dataframes, multi-model inference, anomaly detection, and others. All of these guides come with corresponding Jupyter notebooks [2] for users to easily try them out. Please check them out and let us know if they have been useful. We’ll continue to expand on this work, building guides for more use cases, such as very large models (>30GB!), complex streaming inference, cross-language inference, and more. Stay tuned! Thanks, Aizhamal [1] https://beam.apache.org/documentation/ml/overview/ [2] https://github.com/apache/beam/tree/master/examples/notebooks/beam-ml
