Hello, everyone. It's Gaby again.
Here with my summary of some important points on Machine Learning basics on GCP:
Reference Sources
1. AI Platform Documentations at Google Cloud https://cloud.google.com/ai-platform/docs/technical-overview
2. Data Engineering with Google Cloud Professional Certificate at Coursera https://www.coursera.org/professional-certificates/gcp-data-engineering?
3. Data Engineer Certification Exam Guide at Google Cloud https://cloud.google.com/certification/guides/data-engineer
4. Wide & Deep Learning: Better Together with TensorFlow at Google AI Blog https://ai.googleblog.com/2016/06/wide-deep-learning-better-together-with.html
5. Google Cloud Professional Data Engineer Practice Test at Udemy https://www.udemy.com/course/google-cloud-professional-data-engineer/
6. Google Professional Data Engineer (GCP) Practice Exam at TestPrep https://www.testpreptraining.com/certified-professional-data-engineer-practice-exam
If you are interested in how to implement a ML model on GCP in the fastest way, you can check my previous post of [GCP] Train an Image AutoML Model ( https://www.supertasteofdata.com/post/gcp-train-image-automl-model )
Message or email me if you have any further questions. I will be happy to share my experience with you!
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