Taking on the ML pipeline challenge: why data scientists need to own their ML workflows in production

• zenml

  33 3,657 9.8 Python

  ZenML 🙏: Build portable, production-ready MLOps pipelines. https://zenml.io.

  

ZenML is an open-source MLOps Pipeline Framework built specifically to address the problems above. Let’s break it down what a MLOps Pipeline Framework means:

• neptune-client

  24 531 9.6 Python

  📘 The MLOps stack component for experiment tracking

  

So, if you even want to use MLFlow to track your experiments, run the pipeline on Airflow, and then deploy a model to a Neptune Model Registry, ZenML will facilitate this MLOps Stack for you. This decision can be made jointly by the data scientists and engineers. As ZenML is a framework, custom pieces of the puzzle can also be added here to accommodate legacy infrastructure.

• WorkOS

  workos.com sponsored

  The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.

  

• MLflow

  56 17,234 9.9 Python

  Open source platform for the machine learning lifecycle

  

So, if you even want to use MLFlow to track your experiments, run the pipeline on Airflow, and then deploy a model to a Neptune Model Registry, ZenML will facilitate this MLOps Stack for you. This decision can be made jointly by the data scientists and engineers. As ZenML is a framework, custom pieces of the puzzle can also be added here to accommodate legacy infrastructure.

• Airflow

  169 34,485 10.0 Python

  Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

  

So, if you even want to use MLFlow to track your experiments, run the pipeline on Airflow, and then deploy a model to a Neptune Model Registry, ZenML will facilitate this MLOps Stack for you. This decision can be made jointly by the data scientists and engineers. As ZenML is a framework, custom pieces of the puzzle can also be added here to accommodate legacy infrastructure.

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