InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Elastic Data Analytics Platform @Datadog
Doug Daniels discusses the cloud-based platform they have built at DataDog and how it differs from a traditional datacenter-based analytics stack, pros and cons and the tooling built.
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Petabytes Scale Analytics Infrastructure @Netflix
Tom Gianos and Dan Weeks discuss Netflix' overall big data platform architecture, focusing on Storage and Orchestration, and how they use Parquet on AWS S3 as their data warehouse storage layer.
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Big Data in the Real World: Technology and Use Cases
Mike Olson presents several use cases where big data is collected and analyzed to gather insights from the automotive, insurance, financial, and other sectors.
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Using Bayesian Optimization to Tune Machine Learning Models
Scott Clark introduces Bayesian Global Optimization as an efficient way to optimize ML model parameters, explaining the underlying techniques and comparing it to other standard methods.
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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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