Beyond Deployment: Exploring Machine Learning Inference Architectures and Patterns
Tim Elfrink

"Beyond Deployment: Exploring Machine Learning Inference Architectures and Patterns" - uncover the ML inference strategies that power StepStone's success and learn to scale your models with confidence!

DDataflow: An open-source end-to-end testing framework for ML pipelines
Theodore Meynard, Jean Machado

Explore our talk on DDataflow, a tool transforming ML pipeline testing. It streamlines the process with decentralized data sampling, tackling prolonged development and latent errors in large, complex datasets.

Streamlining Python Development: A Practical Approach to CI/CD with GitHub Actions
Artem Kislovskiy

Learn how continuous integration/delivery boosts project resilience to Python updates and packaging changes. Automate for peace of mind, better code, and seamless collaboration.

The key to reliability - Testing in the field of ML-Ops
Gunar Maiwald, Tobias Senst

idealo.de presents its holistic approach for testing in machine learning

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