Abstract: 

This session will give a brief intro into Computer Vision and jump straight into real world examples. We will keep the learning practical by walking through a number of projects in manufacturing, agriculture, retail, and home insurance, with takeaways that will be applicable to any organization and use case. Some common pitfalls around image models building and evaluating will be demonstrated as well as how to get around them.

Session Outline
Introduction to Computer Vision, Interesting Problems
Quick feature of Visual AI
Image models explainability using real data
Q&A (Last 15 mins of 75 mins slot)

Background Knowledge
Computer Vision experience will help but is not required

Bio: 

Ivan Pyzow is a deep learning engineer at DataRobot on the Visual AI team, focused on implementing state-of-the-art techniques in features that are accessible to a wide range of data scientists. Ivan has worked as a data scientist and engineer at McMaster-Carr Supply and McKinsey & Company, where he built production pipelines for neural networks for search engines, fraud detection systems, and satellite monitoring for agriculture.