Meetup: Cyber and AutoML - Running Machine Learning at Scale

Features for Building a Data Loss Prevention (DLP) System

Ofer Rahat

Target’s infamous breach marked one of the most influential cyber attacks of all times when some 40 million credit card numbers were stolen and sold in the darknet (fall 2013). To perform such an attack, a control and command (C&C or C2) server was placed outside the corporate network to control corporate computers. In this talk, I’ll describe details of modern covert communication channels established for malicious intentions, and describe two algorithms for a Data Loss Prevention (DLP) system.

Running AutoML at Scale

Gilad Ivry (Whatify)

AutoML is the process of building data pipelines and training machine learning models by running multiple experiments with different sets of ML algorithms and hyperparameters.

In this talk, we’ll cover the journey of building a cloud-native, distributed system that offers AutoML capabilities, and the many interesting engineering challenges we’ve met along the way.

Senior Data Scientist

Backend Group

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