Introducing MLOps.toys

We launched a new open-source website called MLOps.toys – a curated list of the most useful MLOps tools and projects for training orchestration, experiment tracking, data versioning, model serving, model monitoring, and explainability.

Because every data science and ML engineering team should have the tools they need to create a strong machine learning infrastructure that supports their end-to-end MLOps needs. Uber, Netflix, Airbnb aren’t the only ones who can build their own machine learning platforms. It’s easier than you might think.

Whether it’s for experiment management, data versioning, serving platforms, or another part of the ML pipeline – we all have different needs and there are TONS of tools to support the ML infrastructure.

But many of these solutions overlap with each other, and it’s difficult to know how to start comparing them in order to find your ideal solution.

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