Build and Monitor Computer Vision Models with TensorFlow 2.0 + WhyLabs

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Build and Monitor Computer Vision Models with TensorFlow 2.0 + WhyLabs

How to build and perform ML monitoring with computer vision classification models in production.

When and where

Date and time



About this event

  • 1 hour
  • Mobile eTicket

Join this hands-on workshop to learn ML monitoring for computer vision models in production with TensorFlow and WhyLabs.

If you want to build reliable computer vision pipelines, trustworthy data, and responsible ML models, you’ll need to monitor your models and data.

In this workshop, we’ll cover how to use ML monitoring techniques to implement your own AI observability solution for computer vision classification applications.

This workshop will cover:

  • Reading image data for TensorFlow models
  • Training a computer vision classification model with TensorFlow 2.0
  • Detecting image data quality issues
  • Detecting data drift for computer vision
  • Measuring for potential concept drift
  • Monitoring ML model performance

What you’ll need:

  • A modern web browser
  • A Google account (for saving a Google Colab)
  • Sign up free a free WhyLabs account (

Who should attend:

Anyone interested in AI Observability, Model monitoring, MLOps, and DataOps! This workshop is designed to be approachable for most skill levels. Familiarity with machine learning and Python will be useful, but it's not required.

By the end of this workshop, you’ll be able to implement data and AI observability into your own pipelines (Kafka, Airflow, Flyte, etc) and ML applications to catch deviations and biases in data or ML model behavior.

About the instructor:

Sage Elliott enjoys breaking down the barrier to AI observability, talking to amazing people in the Robust & Responsible AI community, and teaching workshops on machine learning. Sage has worked in hardware and software engineering roles at various startups for over a decade.

Connect with Sage on LinkedIn:

About WhyLabs: is an AI observability platform that prevents data & model performance degradation by allowing you to monitor your data and machine learning models in production.

Do you want to connect with the team, learn about WhyLabs, or get support? Join the WhyLabs + Robust & Responsible AI community Slack: