From Jupyter Notebook to deployed application in 4 steps

1. jupyter-to-kitops

   1 1 1 4.9 Jupyter Notebook

   Move your machine learning projects from Jupyter Notebook to a deployed application, using ModelKit.

   

   - **A container registry:** You can use [the GitHub Package](https://docs.github.com/en/packages/learn-github-packages/introduction-to-github-packages) registry, [GitLab registry](https://docs.gitlab.com/ee/user/packages/container_registry/), or [DockerHub](https://hub.docker.com/). In this article, you will make use of the GitHub Package registry. - **Code hosting platforms:** You can use GitHub or GitLab. This article uses GitHub. [Here](https://github.com/Techtacles/jupyter-to-kitops) is a link to the code samples used.

2. CodeRabbit

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3. Jenkins

   2 189 23,763 9.9 Java

   Jenkins automation server

   

   CI/CD comes to the rescue. It allows you to build, test, and deploy your models across several environments, such as development, acceptance, and production. Tools like Jenkins, GitHub Actions, and GitLab CI make this easy and convenient.

4. hub-feedback

   3 435 238 2.6

   Feedback and bug reports for the Docker Hub

   

   - **A container registry:** You can use [the GitHub Package](https://docs.github.com/en/packages/learn-github-packages/introduction-to-github-packages) registry, [GitLab registry](https://docs.gitlab.com/ee/user/packages/container_registry/), or [DockerHub](https://hub.docker.com/). In this article, you will make use of the GitHub Package registry. - **Code hosting platforms:** You can use GitHub or GitLab. This article uses GitHub. [Here](https://github.com/Techtacles/jupyter-to-kitops) is a link to the code samples used.

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