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Automatic Training, Testing, and Deployment of AI using CI/CD

  1. 0

    Automatic Training, Testing, and Deployment of AI Using MLOps: Overview

    In this article series, we'll demonstrate how to take use a CI/CD pipeline - a tool usually used by developers and DevOps teams - and demonstrate how to use it to create a complete training, test, and deployment pipeline for AI that meets the requirements of level 2 in the Google MLOps Maturity
    Added 4 May 2021
  2. 1

    Setting Up GitHub, Docker, and Google Cloud Platform for Automated MLOps

    In this article, we set up a cloud environment for this project.
    Added 4 May 2021
  3. 2

    Model Auto-Adjustment in an MLOps Pipeline

    In this article, we’ll implement automatic training.
    Added 5 May 2021
  4. 3

    Continuous Training in an MLOps Pipeline

    In this article, we’ll deep-dive into the Continuous Training code.
    Added 6 May 2021
  5. 4

    MLOps Continuous Delivery with Model Unit Testing

    In this article, we develop a model unit testing container.
    Added 7 May 2021
  6. 5

    Building an MLOps Model API

    In this article we build the model API to support the prediction service.
    Added 10 May 2021