InfoQ Homepage Global Data Science Conference 2017 Content on InfoQ
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Solving Business Problems Using Predictive Analytics
The panelists discuss solving business problems with predictive analytics.
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Fighting Online Fraud and Abuse with Large-Scale Machine Learning at Sift Science
Jacob Burnim discusses Sift’s approach to building a ML system to detect fraud and abuse, including training models, handling imbalanced classes, sharing learning, measuring performance, etc..
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Best Trade-off Point Algorithm for Efficient Resource Provisioning in Hadoop
Peter Nghiem presents the Best Trade-off Point method and algorithm with mathematical formulas for obtaining the exact optimal number of task resources for any workload running on Hadoop.
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Causal Modeling Using Software Called TETRAD V
Suchitra Abel introduces TETRAD and some of its components used for causal modeling to find out the proper causes and effects of an event.
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Precision Measurements in eCommerce
Jennifer Prendki showcases how precision measurements will allow companies like Walmart to deliver a more personalized experience in eCommerce through the combination of Big Data and hard science.
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Solving Business Problems with Data Science
The panelists discuss how companies can use data science to solve various business problems.
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When Models Go Rogue: Hard Earned Lessons on Using Machine Learning in Production
David Talby summarizes best practices & lessons learned in ML, based on nearly a decade of experience building & operating ML systems at Fortune 500 companies across several industries.
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Causal Inference in Data Science
Amit Sharma discusses the value of counterfactual reasoning and causal inference, demonstrating that relying on predictive modeling based on correlations can be counterproductive.
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Large Scale Machine Learning for Payment Fraud Prevention
Venkatesh Ramanathan presents how advanced machine learning algorithms such as Deep Learning and Gradient Boosting are applied at PayPal for fraud prevention.
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AI as a Service at Scale: Retail Case Study
Eldar Sadikov discusses emerging applications of AI in retail, illustrating how Jetlore's machine learning rank technology is currently utilized to power millions of consumer experiences every day.
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AI in Medicine
Anthony Chang presents the past of AI in medicine, the current development status, and what to expect from the future.
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Fast, Scalable, Reusable: A New Perspective on Production ML/AI Systems
Ekrem Aksoy discusses why production ML/AI systems should have a different perspective than the usual DevOps perspective which works on data immune systems.
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