Google AI Platform vs Neuro
Overview
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Detailed Comparison
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. | It accelerates ML development. It provides an instant infrastructure for your ML projects. You can think of it as the Heroku of MLOps or the AWS lambda functions for ML, all powered by GPUs. |
“No lock-in” flexibility;
Supports Kubeflow;
Supports TensorFlow;
Supports TPUs;
Build portable ML pipelines;
on-premises or on Google Cloud;
TFX tools | Wide ML library support;Immediate access to GPUs; Scale as you go; Only pay for compute time |
Statistics | |
Stacks 49 | Stacks 2 |
Followers 119 | Followers 4 |
Votes 0 | Votes 0 |
Integrations | |
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