InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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From Batch to Streaming to Both
Herman Schaaf talks about Skyscanner’s journey to implement their data platform to stream and store millions of events per second.
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Kafka: A Modern Distributed System
Tim Berglund covers Kafka's distributed system fundamentals: the role of the Controller, the mechanics of leader election, and the role of Zookeeper today and in the future.
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We Also Can Do It! Machine Learning in Javascript!
Eliran Eliassy shows how to create a prediction model with a web application using TensorFlow.js and other deep learning tools that can run in the browser.
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You Can AI Like an Expert
Jon McLoone shows that symbolic representation also helps in automating the transition from research experiments to the production deployment of AI services.
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Machine Learning on Mobile and Edge Devices with TensorFlow Lite
Daniel Situnayake talks about how developers can use TensorFlow Lite to build machine learning applications that run entirely on-device.
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Privacy Architecture for Data-Driven Innovation
Nishant Bhajaria discusses how to set up a privacy program and shares tips on how to influence engineering and other teams to own their data and its usage so that privacy is a shared goal.
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Real-Time Live Soccer Score Streaming Application Demo with Reactive Spring Stack
Erdem Gunay demos an application built on Reactive Spring, showing how to persist and query data from Redis, and how to stream live score events in real-time using Kafka.
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Spring Data to Spring Cloud to Spring Security: How Azure Supercharges Spring Boot
Richard Seroter, Asir Selvasingh and Vaibhav Agrawal demo an application that features Spring Security for Azure AD, Spring Cosmos DB, Spring Stream Binder for Event Hubs, Azure Monitor, and others.
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From POC to Production in Minimal Time - Avoiding Pain in ML Projects
Janet Bastiman describes how turning an AI proof of concept into a production ready, deployable system can be a world of pain, especially if different parts of the puzzle are done by different teams.
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Real-Time Data Streaming with Azure Stream Analytics
Alexander Slotte introduces Azure Stream Analytics, its ecosystem, and real world examples streaming Twitter feeds as well as sensor data from Raspberry Pi.
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What Does It Mean to Be a Data Scientist? Definitions and Lessons Learned from the Trenches
Brian Korzynski discusses what Data Science and Big Data are, focusing on the data preparation that needs to take place, and making a distinction between ML issues and programming.
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Big Data Legal Issues. GDPR and Contracts
Anton Tarasiuk discusses the legal issues that can be encountered when dealing with Big Data, GDPR and contracts.
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