Review a serverless application architecture that uses several GCP machine learning (serverless) APIs.
- [Instructor] This next model,…which is a reference architecture using…Google Cloud machine learning services,…is increasing in complexity, but…it has several patterns that I think are interesting.…The use case is creating a series…of machine learning classifiers to categorize…help desk or support tickets.…So as we progress through the architecture,…you can see on the left side, we have a user…and the information goes into a firebase database…when they have a request for support.…This is associated with server-less cloud function,…which then triggers subsequent actions,…and you can see the enrichment and the create…ticket are both handled with cloud functions.…
One aspect of this architecture…that I think is significant in addition…to using multiple machine learning services…is the fact that it is entirely server-less,…so it can scale very, very easily…because Google handles the scaling of course,…because you're not dealing with containers or VMs.…So in addition to the cloud function compute…aspect of this architecture, we have multiple…
- Hosting options: Serverless, containers, and virtual machines
- Enabling the GCP ML AIs
- Preparing data with Cloud Dataflow and Dataprep
- Modeling predictions for images, video, text to speech, and cloud translation
- Machine learning with AutoML
- Advanced machine learning and deep learning
- Machine learning architectures
Skill Level Intermediate
1. Machine Learning on Google Cloud Platform
2. Machine Learning API Services
3. Machine Learning with AutoML
Understand AutoML Vision4m 57s
4. Advanced Machine Learning
5. Machine Learning Architectures
Next steps1m 30s
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