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Noa has been working with data for over a decade, both in academia and in the tech industry. She has thorough, academic-level knowledge of math and statistics, as well as practical experience designing and building machine learning models for production systems.

In her spare time she leads the Israeli community of Women in Data Science, utilizes deep learning techniques for whale research at the Deep Voice foundation, and mentors junior data scientists taking their first steps in the field.

Read more at www.weissnoa.com.

Noa Weiss

AI & Machine Learning Consultant
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English, Hebrew
Tel Aviv, Israel
Can also give an online talk/webinar


The Unspoken Problems With Machine Learning in Security

Data / AI / ML, Security / Privacy

Machine Learning is the hottest buzzword. Everybody loves it, everybody sells it. But why is it that while fields such as Computer Vision or Natural Language Processing have stellar achievements, with new record-breaking models published every other week, the Cybersecurity industry staggers behind?

Are Anomaly Detection algorithms – so well beloved for the prevention of attacks and of fraud - really suitable for those intended purposes? What price do we pay for keeping things hushed? Where do our huge datasets fail us? And how might we try and solve that?

In this talk I will go over several points that hold us back, among them: our rapidly changing input data, and who’s to blame for it; the known issues of imbalanced & untagged datasets, and why our solutions for them are insufficient; and, finally, the biggest culprit: the confidential nature of our field, and how it keeps us from being great.

The unspoken problems with Machine Learning in security: let’s talk about them.

10 Must-Know Concepts in Machine Learning

Data / AI / ML

Do you often find yourself in meetings with obscure machine learning terms thrown all around you, and no idea what they mean? There is hope yet. Designed for tech professionals, this talk introduces 10 must-know concepts in ML, giving you the basic tools to better understand the work around you. Rock the next water cooler chat with your newfound knowledge of these fundamentals of machine learning!

Real-World Problems With Real-World Data

Data / AI / ML

Machine learning courses are all fun and games, but once you hit your first real job, new problems start rolling in. What to do if you don't have enough data? Who might listen to your plea for more "ground truth" labels? And what does this all have to do with a vacation in the tropics? Join Noa Weiss, an AI & Machine Learning consultant, to hear more about those real-world problems that come with real-world data, and how to tackle them like a pro.

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