Michael Press

Building Applications to Unify Data, Cloud, and Smart Analytics

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Gone are the days you had years, or even months, to design and build a solution using AI/machine learning, data analytics, dashboards, and data-driven insights to make informed business decisions. At SpringML, our technical experience allows us to harness the speed and flexibility of the latest cloud technology to create an application that can adapt rapidly …

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Building-Applications-to-Unify-Data,-Cloud,-and-Smart-Analytics

SpringML’s top 5 takeaways from the Google Data Cloud Summit’22

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Recently I had the opportunity to present at the Google Data Cloud Summit. This conference focused on how the next wave of data solutions can allow organizations to make smarter decisions and solve complex challenges using AI, machine learning, analytics, and databases. So (surprise), I described how SpringML partnered with Google Cloud to allow the State …

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SpringML's Top 5 Takeaways..Data Cloud Summit'22

A Comparison of Kubeflow & TFX(TensorFlow Extended)

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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.

Comparison of Kubeflow & TFX
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