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Google AI Platform

Create your AI applications once, then run them easily on both GCP and on-premises
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What is 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.
Google AI Platform is a tool in the Machine Learning as a Service category of a tech stack.

Who uses Google AI Platform?

Companies
7 companies reportedly use Google AI Platform in their tech stacks, including Postclick, Broadsheet, and penelope.

Developers
25 developers on StackShare have stated that they use Google AI Platform.

Google AI Platform Integrations

TensorFlow, Google BigQuery, Google Cloud Storage, Kubeflow, and Google Cloud Dataflow are some of the popular tools that integrate with Google AI Platform. Here's a list of all 6 tools that integrate with Google AI Platform.

Google AI Platform's Features

  • “No lock-in” flexibility
  • Supports Kubeflow
  • Supports TensorFlow
  • Supports TPUs
  • Build portable ML pipelines
  • on-premises or on Google Cloud
  • TFX tools

Google AI Platform Alternatives & Comparisons

What are some alternatives to Google AI Platform?
Kubeflow
The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.
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 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
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
Build And Run Predictive Applications For Streaming Data From Applications, Devices, Machines and Wearables
See all alternatives

Google AI Platform's Followers
97 developers follow Google AI Platform to keep up with related blogs and decisions.