This course teaches how to build an application using serverless technology and machine learning. The learning outcomes include composing an application with serverless components, training an ML model with minimal data, and applying it in an application. The course covers skills such as using Knative, Dialogflow, Cloud Run, Docker, and Container Registry. The teaching method includes presentations, demonstrations, and real-world examples. The intended audience for this course is developers interested in serverless technology, machine learning, and application development.
How We Built Google Tulip by Using Serverless Technology and Machine Learning
Overview
Syllabus
Introduction
Meet Matt Feigal
What is Tulip Translator
Machine Learning
Gathering Data
Training the Model
Evaluating the Model
Testing the Model
Future of Google Tulip
Cristian Hees
The most important part
Im a developer
Cloudrun
Docker
Container Registry
Build Trigger
The Real World
Deployment
How does this work
Dialogue Flow
Demo
How we built
Creating a request
Wrapping up
Github
Taught by
GOTO Conferences
