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our first speaker is going to be uh Phil Tully talking about ranking relevant malware strings using weak supervision Lt Phil received his a joint PhD from the University of Edinburgh in the Royal Institute of Technology he is currently a staff data scientist of fire i working on categorizing malware and social media disinformation great thank you all right so just a few bookkeeping things at first this this was a project that was a collaboration internally at fire between the fire labs reverse engineering team Iamp;#39;m gonna talk to you about how we can take the domain knowledge of those reverse engineers and in inject it directly into our models thatamp;#39;s gonna kind of how Iamp;#39;m gonna argue how we use weak supervision today to solve this problem and then also the data science team which on a member of thereamp;#39;s a bunch of us here weamp;#39;re hiring data scientists across the experience experience spectrum so if youamp;#39;re interested in this talk or any other
