From the course: Data Science on Google Cloud Platform: Predictive Analytics
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Cloud ML Engine - Google Cloud Tutorial
From the course: Data Science on Google Cloud Platform: Predictive Analytics
Cloud ML Engine
- [Narrator] Cloud Machine Learning Engine is the code machine learning product on the GCP platform. It is absolutely the focus for the rest of this course. Cloud ML Engine provides an infrastructure for building your own models, deploying them on GCP, and using them for predictive analytics at GCP scale. You can build models exactly how you would do in an enterprise environment, but deploy them and use them at cloud scale on the ML Engine. Cloud ML Engine supports multiple machine learning environments including scikit-learn, XGBoost, scikit-learn, XGBoost, Keras, and TensorFlow. You can use any of these environments and their supported programming languages for building your models. As with other GCP products, ML Engine's resources are fully managed. There is no virtual machine setup or management work required. ML Engine supports versions. It is possible to have multiple versions of the same model at any time, and use them simultaneously. For clients, ML Engine supports multiple…
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