As machine learning practitioners, we’ve all been there: a model performs brilliantly in testing, only to falter in real-world deployment. Why? Often, it’s due to distribution shift.

In this 30-minute webinar, I help you:

• Understand the critical impact of distribution shift on CV models
• Learn to identify and mitigate performance degradation in real-world applications
• Discover strategies to build more robust and reliable AI systems

Who should watch?

• Startup founders developing the next big breakthrough
• Technical leaders of computer vision projects
• AI researchers interested in model generalization
• Data scientists tackling real-world deployment challenges

This isn’t just theory – we’ll explore real-world examples where distribution shift has caused significant problems, from remote sensing to medical imaging.

For a deeper dive into this topic, check out my team workshop: Mastering Distribution Shift in Computer Vision.