InfoQ Homepage Presentations
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Solving Payment Fraud and User Security with ML
Soups Ranjan talks about Coinbase’s risk program that relies on machine learning (supervised and unsupervised), rules-based systems as well as highly-skilled human fraud fighters.
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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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Evaluating Machine Learning Models: A Case Study
Nelson Ray talks about on how to estimate the business impact of launching various machine learning models, in particular, those Opendoor uses for modeling the liquidity of houses.
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Deep Learning @Google Scale: Smart Reply in Inbox
Anjuli Kannan describes the algorithmic, scaling, deployment considerations involved in a an application of cutting-edge deep learning in a user-facing product: the Smart Reply feature of Google Inbox
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Semi-Supervised Deep Learning on Large Scale Climate Models
Prabhat presents NERSc’s results in applying Deep Learning for supervised and semi-supervised learning of extreme weather patterns, scaling Deep Learning to 9000 KNL nodes on a supercomputer.
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API Design Lessons Learned: Enterprise to Startup
Mohamed El-Geish explores lessons learned at big companies like Microsoft and LinkedIn, and adapts the insights drawn from them to fit a fast-growing startup.
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Beyond REST: Coursera's Journey to GraphQL
Bryan Kane talks about why Coursera is transitioning to GraphQL and shares challenges and learnings from building their GraphQL assembly layer.
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Rethinking CodeGen: IDL, Thrift, gRPC, Ohh My
Cameron Waeland discusses the evolution of Compass and presents their extensible code generation framework which is at the heart of their automatically generated REST to gRPC reverse proxy.
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Hardware & Provisioning Engineering @Twitter
M. Singer and N. Johnson present the Provisioning Engineering system at Twitter, called Wilson, which together with Audubon is designed to handle every part of a server's lifecycle.
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Welcome inside the Head of Larry Wall
Larry Wall is interviewed by Joe Armstrong to find out what goes on inside the head of a programming language designer. Is there a method to use when designing a new language?
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Leaders at All Levels
Esther Derby explores a different definition of leadership: “The ability to enhance the environment, so that everyone is empowered to contribute creatively to solving the problem(s).”
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What is Reactive Programming?
Evgeny Poberezkin discusses the evolution of both the definition and implementations of Reactive Programming and how they have been converging in building responsive applications.
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