Walkthrough on building a Q and A pipeline using various tools, and distributing it with ModelKits for collaboration.
Explores KitOps, an open source project that bridges the gap between DevOps and machine learning pipelines by allowing you to leverage existing DevOps pipelines for MLOps tasks.
ModelKits are standardized packages that contain all the necessary components of an ML project, including the model, datasets, code, and configuration files.
ModelKits are defined using a YAML file called a Kitfile, which can be integrated seamlessly with existing DevOps pipelines, much like a Dockerfile for containerization.
ModelKits are standardized packages that contain all the necessary components of an ML project, including the model, datasets, code, and configuration files.
ModelKits are defined using a YAML file called a Kitfile, which can be integrated seamlessly with existing DevOps pipelines, much like a Dockerfile for containerization.
