How we Built Google Tulip by using Serverless Technology and Machine Learning
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How to compose an application of multiple serverless components. Training an ML model for your needs with minimal training data and applying it in your application. **What will the audience learn from this talk?**<br> How to compose an application of multiple serverless components. Training an ML model for your needs with minimal training data, and applying it in your application. Building and running your code in serverless Knative Using Dialogflow to power user conversations. **Does it feature code examples and/or live coding?**<br> It features live demos of our components and end product. We’ll show code and run scripts to train ML models and deploy our code. **Prerequisite attendee experience level:** <br> [Level 100](https://gotoams.nl/2019/pages/experience-level)
Transcript
How to compose an application of multiple serverless components. Training an ML model for your needs with minimal training data and applying it in your application.
What will the audience learn from this talk?
How to compose an application of multiple serverless components. Training an ML model for your needs with minimal training data, and applying it in your application. Building and running your code in serverless Knative Using Dialogflow to power user conversations.
Does it feature code examples and/or live coding?
It features live demos of our components and end product. We’ll show code and run scripts to train ML models and deploy our code.
Prerequisite attendee experience level:
Level 100
About the speakers
Customer Engineer at Google Cloud
Cloud Customer Engineering Manager for Benelux
Customer Engineer at Google