InfoQ Homepage Real Time Content on InfoQ
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Engineering Systems for Real-Time Predictions @DoorDash
Raghav Ramesh presents DoorDash’s thoughts on how to structure ML systems in production to enable robust and wide-scale deployment of ML, and shares best practices in designing engineering tooling.
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ML Data Pipelines for Real-Time Fraud Prevention @PayPal
Mikhail Kourjanski focuses on the architectural approach towards PayPal’s real-time service platform that leverages ML models, delivers performance and quality of decisions.
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Real-Time Data Analysis and ML for Fraud Prevention
Mikhail Kourjanski addresses the architectural approach towards the PayPal internally built real-time service platform, which delivers performance and quality of decisions.
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Data Pipelines for Real-Time Fraud Prevention at Scale
Mikhail Kourjanski discusses the architecture of PayPal’s data service which combines a Big Data approach with providing data in real time for decision making in fraud detection.
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Adding Real-Time Features to Your Applications with SignalR
Javier Lozano introduces SignalR and covers the features and approaches SignalR offers on both client and server sides.
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Real-Time Data Activation - Analytics, Intelligence & Decision Making
Marcelo Wiermann discusses dealing with real-time analytics with the Lambda Architecture, creating a working data set and data-driven features in an application.
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Data Decisions with Real-Time Stream Processing
Serhat Yilmaz talks about how Facebook is using stream processing at scale, the difficulties they have encountered and the solutions they have created to date.
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Enabling High Performance Real-time Analytics for IoT Environments
Mahish Singh discusses how to use methodologies during design, development, deployment and operation for delivery of analytics platforms which offer real-time SLAs.
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Real-Time & Personalized Notifications @Twitter
Gary Lam and Saurabh Pathak talk about the hybrid push/pull-based architecture adopted by Twitter Notification platform.
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Extreme Programming Meets Real-time Data
Tom Johnson and Gel Goldsby talk about scaling problems they encountered at Unruly, and where extreme programming values led them.
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The Move to AI: from HFT to Laplace Demon
Eric Horesnyi and Albert Bifet discuss how hedge funds have moved beyond High Frequency Trading using AI and real-time data processing.
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ETL Is Dead, Long Live Streams
Neha Narkhede shares the experience at LinkedIn moving from ETL to real-time streams, the challenges of scaling Kafka to hundreds of billions of events/day, supporting thousands of engineers, etc.