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API StatusChangelog
Cloud AI Platform Pipelines
ByCloud AI Platform PipelinesCloud AI Platform Pipelines

Cloud AI Platform Pipelines

#160in Text & Language Models
Stacks0Discussions0
Followers6
OverviewDiscussions

What is Cloud AI Platform Pipelines?

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.

Key Features

Push-button installation via the Google Cloud ConsoleEnterprise features for running ML workloads, including pipeline versioning, automatic metadata tracking of artifacts and executions, Cloud Logging, visualization tools, and moreSeamless integration with Google Cloud managed services like BigQuery, Dataflow, AI Platform Training and Serving, Cloud Functions, and many othersMany prebuilt pipeline components (pipeline steps) for ML workflows, with easy construction of your own custom components

Cloud AI Platform Pipelines Pros & Cons

Pros of Cloud AI Platform Pipelines

No pros listed yet.

Cons of Cloud AI Platform Pipelines

No cons listed yet.

Cloud AI Platform Pipelines Alternatives & Comparisons

What are some alternatives to Cloud AI Platform Pipelines?

Amazon SageMaker

Amazon SageMaker

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

Azure Machine Learning

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.

Amazon Machine Learning

Amazon 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.

Algorithms.io

Algorithms.io

Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables

Replicate

Replicate

It lets you run machine learning models with a few lines of code, without needing to understand how machine learning works.

Google AI Platform

Google AI Platform

Makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively.

Cloud AI Platform Pipelines Integrations

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.

Google BigQuery
Google BigQuery
Google Cloud Functions
Google Cloud Functions
Google Cloud Dataflow
Google Cloud Dataflow
Google Kubernetes Engine
Google Kubernetes Engine
Google AI Platform
Google AI Platform

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