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Presentation: Policing the Capital Markets with ML

Track: Solving Software Engineering Problems with Machine Learning

Location: Cyril Magnin III

Duration: 9:00am - 9:40am

Day of week: Wednesday

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Abstract

Cliff Click talks about SCORE, a solution for doing Trade Surveillance using H2O, Machine Learning, and a whole lot of domain expertise and data munging. SCORE pulls in private and public market data and in a few minutes will search it for all sorts of bad behavior and downright illegal activity. It then filters down the billions of rows of data down to human scale with some great visualizations.

Speaker: Cliff Click

CTO of @CratusTech

Cliff Click was the CTO of Neurensic (now successfully exited), and CTO and Co-Founder of h2o.ai (formerly 0xdata), a firm dedicated to creating a new way to think about web-scale math and real-time analytics. He wrote his first compiler when he was 15 (Pascal to TRS Z-80!), although his most famous compiler is the HotSpot Server Compiler (the Sea of Nodes IR). Cliff helped Azul Systems build an 864 core pure-Java mainframe that keeps GC pauses on 500Gb heaps in the micro-second range, and worked on all aspects of that JVM. Before that he worked on HotSpot at Sun, and is, at least, partially responsible for bringing Java into the mainstream.  Cliff is invited to speak regularly at industry and academic conferences and he holds a PhD in Computer Science and more than 20 patents.

Find Cliff Click at

2019 Tracks

  • Predictive Data Pipelines & Architectures

    Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix

  • Sequential Data: Natural Language, Time Series, and Sound

    Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.

  • ML in Action

    Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud