InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Serverless & GraphQL
Jared Short dives into why, how, and when to pair Serverless & GraphQL, with takeaways for implementing the first greenfield Serverless GraphQL API or migrating existing APIs.
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Streaming SQL Foundations: Why I ❤Streams+Tables
Tyler Akidau explores the relationship between the Beam Model and stream & table theory, stream processing in SQL with Apache Beam, Calcite, Flink, Kafka KSQL and Apache Spark’s Structured streaming.
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The Power of Distributed Snapshots in Apache Flink
Stephan Ewen talks about how Apache Flink handles stateful stream processing and how to manage distributed stream processing & data driven applications efficiently with Flink's checkpoints&savepoints.
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Designing Visualizations for Action
Chris Varosy discusses strategies for designing data visualizations and dashboards that bring the insight users need to make decisions.
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Adding AI Smarts with Cognitive Services
Stephen Bohlen discusses Microsoft’s Cognitive Services, how to use them, exploring services for Facial Recognition, object detection, NLP, as well as Topic Extraction and Sentiment Analysis.
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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