InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
-
Data Consistency in Microservice Using Sagas
Chris Richardson discusses messaging, durability, and reliability in microservice architectures leveraging the Saga Pattern, explaining how sagas work and introduces a saga framework for Java.
/presentations/saga-microservices/en/mediumimage/Cjrisbig-1517455133718.JPG)
-
Automating Netflix ML Pipelines with Meson
Davis Shepherd and Eugen Cepoi discuss the evolution of ML automation at Netflix and how that lead them to build Meson, challenges faced and lessons learned automating thousands of ML pipelines.
/presentations/netflix-ml-meson/en/mediumimage/eugen-davis-big-1516777367854.jpg)
-
Preparing Humans for the Second Machine Age
Dominic Price prepares his listeners for the world of 2020, the role that AI, automation and robots will have, and what people should do to stay human and build an environment where they thrive.
/presentations/tech-2020/en/mediumimage/Dombig-1516418555217.JPG)
-
Data Science for Developers: The Big Picture
Matthew Renze discusses what data science is, why it’s important, and how to prepare for it. He covers IoT, Big Data, ML, and how they are converging to create fully-autonomous intelligent systems.
/presentations/data-science-dev/en/mediumimage/Matbig-1516324183088.JPG)
-
Polyglot Persistence Powering Microservices
Roopa Tangirala takes a look at Netflix’s common platform used to manage, maintain, and scale persistence infrastructures, sharing the benefits, pitfalls, and lessons learned along the way.
/presentations/microservices-polyglot-persistence/en/mediumimage/PolyglotPersistencePoweringMicroservices-1517500898488.jpg)
-
Getting Data Science to Production
Sarah Aerni covers the nuts and bolts of the Einstein Platform, a system that enables the automation and scaling of Artificial Intelligence to 1000s of customers, each with multiple models.
/presentations/einstein-platform-ai/en/mediumimage/Sarbig-1515888330792.JPG)
-
ML for Question and Answer Understanding @Quora
Nikhil Dandekar discusses how Quora extracts intelligence from questions using machine learning, including question-topic labeling, removing duplicate questions, ranking questions & answers, and more.
/presentations/quora-ml/en/mediumimage/Nikbig-1515814953724.JPG)
-
Monitoring Modern Architectures with Data Science
Dave Casper talks about how modern data science and algorithms are being applied to "fight machines with machines".
/presentations/modern-architectures-data-science/en/mediumimage/Davbig-1514519899503.JPG)
-
Bias in BigData/AI and ML
Leslie Miley discusses how inherent bias in data sets has affected things from the 2016 Presidential race to criminal sentencing in the United States.
/presentations/bias-bigdata-ai-ml/en/mediumimage/BiasInBigDataAIAndML-1517493548914.jpg)
-
Handling Billions of Edges in a Graph Database
Michael Hackstein discusses graph databases, the current scalability problems and their solutions.
/presentations/graph-database-scalability/en/mediumimage/Micbig-1513911472792.JPG)
-
Cognitive Services, Next Step in Creating Our Robot Overlords
Harold Pulcher discusses Cognitive Services, how to get started using them, and how to incorporate speech, image, and facial recognition into an application.
/presentations/cognitive-services-introduction/en/mediumimage/Harbig-1513384614768.JPG)
-
Production Machine Learning
Jan Machacek discusses the challenges in writing deep learning code, testing and validating data management, environments, model storage & serving, validating data reporting, and CI&CD.
/presentations/machine-learning-production/en/mediumimage/Janbig-1512873108760.JPG)