Pipeline is a platform for building and deploying machine learning pipelines. With Pipeline.ai, users can create, test, and deploy machine learning models at scale. The platform provides a user-friendly interface for constructing computational graphs for AI/ML, making it suitable for both development and production environments.
To run a complete pipeline on “Pipeline.ai”, users can use the following code:
complete_pipeline = Pipeline.get_pipeline(“MathsIsFun”)
# Instantiate the complete pipeline
complete_pipeline.run(5.0, 6.0)
# Run the pipeline locally
To run this tool in the cloud, the user must import PipelineCloud and instantiate the API with their API token.
This is one of many machine learning pipeline services available. Other options include Google Cloud’s Vertex AI Pipelines, which provides a way to describe ML workflows as pipelines and orchestrate ML processes, and AI Platform Pipelines, also from Google Cloud, which requires defining an ML process as a pipeline before running it on the platform.
In summary, Pipeline is a platform for building and deploying machine learning pipelines, which provides a user-friendly interface for constructing computational graphs for AI/ML. Users can run pipelines locally or in the cloud and can choose from a variety of machine learning pipeline services available.
