mlops-guide/dvc-gitactions
Example project with a complete MLOps cycle: versioning data, generating reports on pull requests and deploying the model on releases with DVC and CML using Github Actions and IBM Watson. Part of the Engineering Final Project @ Insper
This project helps MLOps engineers set up a robust workflow for managing machine learning models. It takes raw data and model code, automates the training and evaluation process, and prepares the model for deployment. The primary users are MLOps engineers or data scientists responsible for operationalizing machine learning models.
No commits in the last 6 months.
Use this if you need to automate your machine learning model lifecycle, including data versioning, continuous integration/delivery, and deployment to cloud platforms like IBM Watson.
Not ideal if you are looking for a simple model training script or a tool for exploratory data analysis rather than a complete MLOps pipeline.
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Nov 23, 2021
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