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Presentation: Measuring Business Impact of Machine Learning System

Track: ML in Action

Location: Cyril Magnin III

Duration: 1:10pm - 2:00pm

Day of week: Tuesday

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Abstract

I will provide an overview of how to do metric driven ML system development, primarily to answer following questions:

  • How do you bootstrap machine learning system for new objectives?
  • How do you tie up the ML system performances with business goals?
  • Do precision & recall always work as primary metrics?
  • How do you measure effectiveness of entire ML system in the context of product success?

These questions will be answered in the context of fraud detection case study.

Speaker: Jevin Bhorania

Cash Data Science Lead @Square

Find Jevin Bhorania at

2019 Tracks

  • Groking Timeseries & Sequential Data

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

  • Deep Learning in Practice

    Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.