Finding Bad Acorns - Andrew Gao & Jeff Sharpe
Flink Forward San Francisco, April 2018 #flinkforward
Finding Bad Acorns - Andrew Gao & Jeff Sharpe
Within fintech catching fraudsters is one of the primary opportunities for us to use streaming applications to apply ML models in real-time. This talk will be a review of our journey to bring fraud decisioning to our tellers at Capital One using Kafka, Flink and AWS Lambda. We will share our learnings and experiences to common problems such as custom windowing, breaking down a monolith app to small queryable state apps, feature engineering with Jython, dealing with back pressure from combining two disparate streams, model/feature validation in a regulatory environment, and running Flink jobs on Kubernetes.
https://data-artisans.com/
Видео Finding Bad Acorns - Andrew Gao & Jeff Sharpe канала Flink Forward
Finding Bad Acorns - Andrew Gao & Jeff Sharpe
Within fintech catching fraudsters is one of the primary opportunities for us to use streaming applications to apply ML models in real-time. This talk will be a review of our journey to bring fraud decisioning to our tellers at Capital One using Kafka, Flink and AWS Lambda. We will share our learnings and experiences to common problems such as custom windowing, breaking down a monolith app to small queryable state apps, feature engineering with Jython, dealing with back pressure from combining two disparate streams, model/feature validation in a regulatory environment, and running Flink jobs on Kubernetes.
https://data-artisans.com/
Видео Finding Bad Acorns - Andrew Gao & Jeff Sharpe канала Flink Forward
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Build a Table-centric Apache Flink Ecosystem - Shaoxuan WangMulti-tenanted streams @Workday - Enrico Agnoli & Leire Fernandez#FlinkForward SF 2017: Ufuk Celebi - The Stream Processor as a DatabaseImproving throughput and latency with Flink's network stack - Nico KruberStreaming for Enterprises - Srikanth SatyaBuilding Unified Streaming Platform at UberAnalytics for the masses - Aslam TajwalaWriting an interactive streaming SQL engine and pre-parser using Flink - Kenny GormanInterview with Gyula Fóra, Data Warehouse Engineer at KingAdventures in Scaling from Zero to 5 Billion Data Points per Day - Dave TorokSplunk Data Stream ProcessorOne SQL to Rule Them All - Fabian HueskeBuilding an open-source ML feature store with Apache FlinkData Pipeline Lifecycle: SQL EverywhereCEP platform handling millions of users - lessons from 3 years in productionWhat turns stream processing from a tool into a platform? - Stephan EwenScotty: Efficient Window Aggregation with General Stream Slicing - Jonas Traub & Philipp GrulichKeeping Redditors safe in real-time with Flink Stateful FunctionsDistributed Processing for Machine Learning Production Pipelines - Altay, Crowe, RokniFlink Forward Berlin 2018 Highlights