GCP datacenters are 100% offset with PPAs. Are you referring to different functionality for costing AutoML instructions in terms of carbon?
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I'd add:
- Setup a Jupyter Notebook environment
> Jupyter Notebooks are one of the most popular development tools for data scientists. They enable you to create interactive, shareable notebooks with code snippets and markdown for explanations. Without leaving Google Cloud's hosted notebook environment, AI Platform Notebooks, you can leverage the power of AutoML technology.
> There are several benefits of using AutoML technology from a notebook. Each step and setting can be codified so that it runs the same every time by everyone. Also, it's common, even with AutoML, to need to manipulate the source data before training the model with it. By using a notebook, you can use common tools like pandas and numpy to preprocess the data in the same workflow. Finally, you have the option of creating a model with another framework, and ensemble that together with the AutoML model, for potentially better results.
https://cloud.google.com/blog/products/ai-machine-learning/u...
