Actionable checklist to verify security configurations in Google Cloud
Actionable checklist to verify security configurations in Google Cloud Read More »
Actionable checklist to verify security configurations in Google Cloud Read More »
Coffee Ordering and Order Refund Automation Using Dialogflow Read More »
SpringML works with Looker to build AI-powered analytics to help enterprises build & scale modern data platforms and realize its benefits.
SpringML’s “AI Visualization Pilot” program helps enterprises quickly realize the value of Tableau and Einstein to inform daily decisions.
SpringML’s Propensity to Buy Accelerator analyzes a customer’s history of purchasing actions and past and current behaviors to predict the likelihood they will buy or become a repeat customer.
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Einstein Accelerator. This Accelerator will enable you to deploy Sales Analytics, review best practice for Salesforce Inbox, and coach your team on how to leverage the other AI features in workflows and operations!
SpringML’s Propensity to Buy Accelerator analyzes a customer’s history of purchasing actions and past and current behaviors to predict the likelihood they will buy or become a repeat customer.
Download SpringML’s Predictive Churn Accelerator to find out how you can get a 360-degree view of your customer to determine the likelihood they will leave, cancel, or choose not to renew.
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.