You can use various tools to define and run machine learning (ML) pipelines or DAGs (Directed Acyclic Graphs). Some popular options include AWS Step Functions, Apache Airflow, KubeFlow Pipelines (KFP), TensorFlow Extended (TFX), Argo, Luigi, and Amazon SageMaker Pipelines. All these tools help you compose pipelines in various languages (JSON, YAML, Python, and more), followed by viewing and running them using a workflow orchestrator. A deep comparison of each of these options is out of scope for this post, and involves appropriately selecting and benchmarking tools for your specific use case.
In this post, we discuss how to author end-to-end …
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