It provides a way to deploy robust, repeatable machine learning pipelines along with monitoring, auditing, version tracking, and reproducibility, and delivers an enterprise-ready, easy to install, secure execution environment for your ML workflows.
Cloud AI Platform Pipelines is a tool in the Text & Language Models category of a tech stack.
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What are some alternatives to Cloud AI Platform Pipelines?
A fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.
Azure Machine Learning is a fully-managed cloud service that enables data scientists and developers to efficiently embed predictive analytics into their applications, helping organizations use massive data sets and bring all the benefits of the cloud to machine learning.
This new AWS service helps you to use all of that data you’ve been collecting to improve the quality of your decisions. You can build and fine-tune predictive models using large amounts of data, and then use Amazon Machine Learning to make predictions (in batch mode or in real-time) at scale. You can benefit from machine learning even if you don’t have an advanced degree in statistics or the desire to setup, run, and maintain your own processing and storage infrastructure.
Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables
Google BigQuery, Google Cloud Functions, Google Cloud Dataflow, Google Kubernetes Engine, Google AI Platform are some of the popular tools that integrate with Cloud AI Platform Pipelines. Here's a list of all 5 tools that integrate with Cloud AI Platform Pipelines.