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Building a machine learning-based ad filter from scratch
Session details

At eyeo we are dedicated to bringing sustainable balance to the internet. For this to work long-term, content creators, publishers and advertisers must be able to fairly monetize but also must do so without compromising the user experience. We think the best way to reach this happy medium is with ad filtering. This inspired us to look into using advanced artificial intelligence (AI) such as machine learning (ML) to tackle one of the main issues for internet users today, how to handle intrusive and inappropriate ads which can invade privacy and disrupt the overall user experience. We set ourselves one huge, crazy goal - a moonshot - to create a minimum viable product (MVP) that implements ML to automate ad detection.

In this talk, I will take you through our journey as we look to revolutionize the way ad detection works. I will share our secrets and lessons of how to build the machine learning pipeline and address challenges from data collection to model training and from deployment to performance evaluation. By the end of this talk, you'll feel equipped to build a machine learning solution for your own applications.

Dr. Humera Noor Minhas
Director of Engineering
Eyeo GmbH
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