Building ML Workflows with Java, Python & Apache Beam

Explore Apache Beam, a powerful framework for building batch and streaming ML workflows with multi-language support. Learn how to orchestrate data processing pipelines using Java and Python components, enabling collaboration between teams with different language preferences. Discover the benefits of creating flexible, scalable workflows that leverage the strengths of various programming languages. Gain insights from Robbe Sneyders, Head of Delivery at ML6, as he shares his expertise in machine learning systems design, representation learning, and MLOps methodology. Dive into practical examples and best practices for implementing Apache Beam in your ML projects, and understand how this framework can enhance your data processing capabilities across different domains.