Live coding a machine learning model from scratch

Agenda:
5:30 - 6:15 networking
6:15 - 7:15 presentation
7:15 - 8:00 networking

Presentation: Live coding a machine learning model from scratch
Speaker: Google Cloud AI/Developer Advocate

Abstract: Do you want to build a machine learning model but aren’t sure where to start? Sara Robinson starts with an empty notebook and live codes a simple neural network in TensorFlow. She demonstrates how to train and serve the model on Google Cloud Platform and uses the deployed model to generate predictions from a web app.

Who is this presentation for?
Developers with minimal machine learning (ML) experience and ML engineers.

Level: Intermediate

Prerequisite knowledge:

• A basic knowledge of Python
• General knowledge of basic machine learning concepts: training, serving, etc. (but not necessarily how to build a model on your own)

What you'll learn:

• Learn how to build a simple neural network
• Understand the end-to-end ML workflow and how to use your trained model for generating predictions

Bio: Sara Robinson is a developer advocate on Google’s Cloud Platform team, focusing on machine learning. She helps developers build awesome apps through demos, online content, and events. Previously, she was a developer advocate on the Firebase team at Google. Sara holds a bachelor’s degree from Brandeis University. When she’s not programming, she can be found on a spin bike, listening to the Hamilton soundtrack, or eating froyo.