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?
7 developers on StackShare have stated that they use Google AI Platform.
Google AI Platform Integrations
TensorFlow, Google Cloud Storage, Google BigQuery, Google Cloud Dataflow, and Kubeflow 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.
Why developers like Google AI Platform?
Here’s a list of reasons why companies and developers use Google AI Platform
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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?
See all alternatives
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.
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.
Amazon Elastic Inference
Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75%. Amazon Elastic Inference supports TensorFlow, Apache MXNet, and ONNX models, with more frameworks coming soon.