
MLOps framework for infrastructure agnostic ML pipelines
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- ZenML helps developers structure code into pipelines, integrate tools, and deploy to the cloud.
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- It enables increased collaboration, modular code for ML projects, and automated Dockerization.
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- It provides observability through a UI, data quality gates, and monitoring for ML pipelines.
- With ZenML, users can easily plug in and track experiments with Python decorators.
- It supports easy definition of data dependencies, alerts, and observability for ML processes.
- ZenML does not impose opinions on orchestration layers and supports various ML orchestrators.
- It integrates with Python ecosystem, major ML infrastructures, and supports LLMOps use-cases.
- ZenML offers open-source core and a cloud product for a collaborative ML experience.
- Endorsed by industry experts for simplifying ML workflows and enabling reproducibility.
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