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In this report, we compare two technologies that have come out of Google for managing machine learning Pipelines. The first is Kubeflow, which has been in development since 2018 and was originated as a way of bringing the ideas of TFX (used only internally at Google at the time) to the public via open source tools and is in the process of changing as many developments as open source tools come and go. The second is TensorFlow Extended (TFX) itself. Google announced that it would be making TFX available to the public at the end of 2018.
Computer scientists have been seriously exploring artificial intelligence — the idea that machines can mimic the cognitive functions of the human brain — for more than 60 years. No longer the stuff of science fiction, AI now has practical applications across industries and functions, and businesses are adopting it for everything from marketing personalization and image classification to supplychain optimization and fraud detection. One technique in particular forms the backbone of many organizations’ AI strategies: machine learning (ML), which uses large volumes of data to train sophisticated algorithms to self-improve.