Cloud AI Services: What they are and how to use them

"Powerful machine learning capabilities are available as Cloud AI services. You can embed off-the-shelf models for vision and natural language processing into your applications with APIs. AutoML can help you build a custom model with a minimum of code. If you do want to build a custom model by hand, there are serverless tools to develop, train, and deploy your model. In this session, we will discuss why and when to use AI services versus training your own model. We will cover differences in data requirements, performance, integration, and ease of use."
Who is this presentation for?
Developers, data scientists, and data engineers
Prerequisite knowledge:
Basic ML and cloud concepts
What you'll learn?
How to build and use machine learning models in the Cloud

Karl Weinmeister is a Cloud AI Advocacy Manager at Google, where he leads a team of data science experts who develop content and engage with communities worldwide. Karl has worked extensively in machine learning and cloud technologies. He was a contributor to one of the first AI-based crossword puzzle solvers that is still referenced today.