InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Machine Learning and End-to-End Data Analysis Processes in Spark Using Python and R
Debraj GuhaThakurta discusses ML and data analysis processes in Spark using examples written in Python and R.
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Machine Learning Your Way to Smarter API Error Responses
Steven Cooper discusses using machine learning to understand malformed API requests to not only respond with a best fit response, but capture the user errors for future responses.
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I Can't Believe It's Not a Queue: Using Kafka with Spring
Joe Kutner talks about Kafka and where it fits in a Spring app and how to make it do things message queues simply can't.
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Streaming Live Data and the Hadoop Ecosystem
Oleg Zhurakousky discusses the Hadoop ecosystem – Hadoop, HDFS, Yarn-, and how projects such as Hive, Atlas, NiFi interact and integrate to support the variety of data used for analytics.
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Scaling the Data Infrastructure @Spotify
Mārtiņš Kalvāns and Matti Pehrs overview the Data Infrastructure at Spotify, diving into some of the data infrastructure components, such us Event Delivery, Datamon and Styx.
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Scaling Counting Infrastructure @Quora
Chun-Ho Hung and Nikhil Garg discuss Quanta, Quora's counting system powering their high-volume near-real-time analytics, describing the architecture, design goals, constraints, and choices made.
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Java (SE) State of the Union
Gil Tene presents the current state of Java SE and OpenJDK, the role of Java in the Big Data and Infrastructure components, JCP, the ecosystem, trends, etc.
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Scaling Quality on Quora Using Machine Learning
Nikhil Garg talks about the various Machine Learning problems that are important for Quora to solve in order to keep the quality high at such a massive scale.
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Query Understanding: a Manifesto
Daniel Tunkelang talks about what search looks like when viewed through a query understanding mindset. He focuses on query performance prediction, query rewriting, and search suggestions.
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Iterative Design for Data Science Projects
Bo Peng goes over how Datascope iterated on the major pieces of the Expert Finder application project to produce actionable insights and recommendations on methodologies.
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The Art of Relevance and Recommendations
Clarence Chio talks about the creation of a real-world relevance and recommendation system from scratch.
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Reactive Kafka
Rajini Sivaram talks about Kafka and reactive streams and then explores the development of a reactive streams interface for Kafka and the use of this interface for building robust applications.
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