Review a chatbot solution architecture that uses multiple types of GCP machine learning services.
- So in this next section, we're going to take a look…at some reference architectures using various types of…GCP machine learning, and we're gonna examine this…through the scenarios within the domains and also…in the types of implementations, and we're…gonna go from simple to complex.…All of these scenarios have implementation code available…and I'll show you where that is as well…so you can actually try them out.…So the first one is a chatbot client.…The idea here is that you wanna…have a conversational application.…
This could be for help desk calls or customer calls…or some kind of interaction in working with customers.…So you can see that the services that are being used…are the Google Cloud APIs for machine learning for…vision, speech, and translation.…So, the high level APIs are what work best for this…scenario because they have very advanced functionality…and you can simply pass the data…to them and get the output that you need.…
Now, in addition to that, cloud functions are being used…as a serverless component and webhooks with an integration…
- 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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