Google Prediction Framework addresses data pipeline drudgery
Google’s Prediction Framework stitches together Google Cloud Platform services, from Cloud Functions to Pub/Sub to Vertex AutoML to BigQuery, to help users implement data prediction projects and save time doing so.Detailed in a December 29 blog post, Prediction Framework was designed to provide the basic scaffolding for prediction solutions and allow for customization. Built for hosting on the Google Cloud Platform, the framework is an attempt to generalize all steps involved in a prediction project, including data extraction, data preparation, filtering, prediction, and post-processing. The idea behind the framework is that with just a few particularizations/modifications, the framework would fit any similar use case, with a high level of reliability.To read this article in full, please click here
Google’s Prediction Framework stitches together Google Cloud Platform services, from Cloud Functions to Pub/Sub to Vertex AutoML to BigQuery, to help users implement data prediction projects and save time doing so.
Detailed in a December 29 blog post, Prediction Framework was designed to provide the basic scaffolding for prediction solutions and allow for customization. Built for hosting on the Google Cloud Platform, the framework is an attempt to generalize all steps involved in a prediction project, including data extraction, data preparation, filtering, prediction, and post-processing. The idea behind the framework is that with just a few particularizations/modifications, the framework would fit any similar use case, with a high level of reliability.
