Gathering the reusable knowledge, concepts, and artifacts for future projects
Your DL projects will result in many artifacts that can be reused in the future. For example, the processed data used during the model training can be reused for other analytical tasks, the model implementation can be adapted to other applications, and the infrastructure set up for monitoring tasks can be reconfigured for different projects. To be able to reuse these artifacts, you need to archive them correctly and ensure that sufficient documentation exists. Let’s have a look at some procedures that you can implement to make your life easier in this process:
- Set up versioning standards for development environments, data, implementations, and models. They should be defined at the early stage of the project, and all the team members should follow them:
- Add versioning for the code base using Git (https://git-scm.com). The project can be linked with GitHub (https://github.com), GitLab (https...
