google ai platform vs ml engine

问题

I did lots of search, but I cannot understand what the difference between google ai platform and ml engine.

It seems that both of them can be used for training and deploying models.

Other words like google-cloud-automl, google ai hub are also very confusing.

What are the differences between them? Thanks

回答1:

The short answer is: there isn't. In 2019 "ML Engine" was renamed to "AI Platform" and in time some services changed and expanded. To see what has changed, check the release notes, starting from around April. "Around", as they haven't left much trace that ML Engine ever existed.

Here's one of pull requests to "Rename Cloud ML Engine to AI Platform" for Python samples.

回答2:

Correct, the previous ML Engine service is now under Cloud AI Platform portfolio of products and provides end-to-end platform to build, run, and manage ML projects.

Please follow the instructions on how to use the service here.

回答3:

Cloud ML Engine = AI Platform Training + AI Platform Prediction (It was just a name change). Used for training and deploying ML models.

AI Platform Training: Bring your own code and submit Training jobs using supported ML frameworks such as TensorFlow, scikit-learn, XGBoost, Keras, etc.
AI Platform Prediction: Host your Model and use AI Platform Prediction to infer target values for new data.

Google Cloud Auto ML = You don't need to code, bring your dataset and GCP automatically picks the best model for you.

Different products: