Posted by HyeJung Lee and MJ You, Google ML Ecosystem Community Managers. Reviewed by Soonson Kwon, Developer Relations Program Manager.
With the initiative and lead of US-based GDE
17 ML GDEs presented at
Meanwhile in Europe, GDEs
On top of her women-in-tech related activities,
Nepal-based GDE
On the other side of the world, in Canada, GDE
We have been equally busy on the GCP side as well. In the US, GDE
Korean GDE
Last but not least, GDE Gad Benram based in Israel wrote an article on “Seven Tips for Forecasting Cloud Costs”, where he explains how to build and deploy ML models for time series forecasting with Google Cloud Run. It is linked with his solution of building a cloud-spend control system that helps users more-easily analyze their cloud costs.
If you want to know more about the Google Experts community and all their global open-source ML contributions, visit the GDE Directory and connect with GDEs on Twitter and LinkedIn. You can also meet them virtually on the ML GDE’s YouTube Channel!
Source: Machine Learning GDEs: Q1 2021 highlights, projects and achievements
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