silverstar0727/ML-Pipeline-Tutorial
TFX와 Kubeflow를 공부한 것을 바탕으로 제작한 튜토리얼입니다.
This project provides a tutorial for building and managing machine learning pipelines. It guides you through setting up workflows that take raw data and machine learning models, processing them into deployable, automated prediction services. This is for data scientists, machine learning engineers, and MLOps practitioners who need to productionize ML models reliably.
No commits in the last 6 months.
Use this if you are a machine learning engineer looking to learn how to build, deploy, and manage ML pipelines using TFX, Kubeflow, or Vertex AI.
Not ideal if you are looking for an out-of-the-box solution to directly solve a business problem rather than a learning resource for pipeline infrastructure.
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Jupyter Notebook
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Last pushed
Oct 05, 2021
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