InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Journey from Data Integration to Data Science
Michael Wise discusses the journey from having data integrated across an organization, to employing data science to make good use of it.
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The Joy of Not Coding
Jeroen Janssens discusses several tricks for polyglot programmers helping to mix and match different languages and tools in a project.
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Applying Big Data
Graeme Seaton discusses the drivers behind Big Data initiatives and how to approach them using the vast amounts of data available.
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Apache Beam: The Case for Unifying Streaming APIs
Andrew Psaltis talks about Apache Beam, which aims to provide a unified stream processing model for defining and executing complex data processing, data ingestion and integration workflows.
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Monitoring and Troubleshooting Real-Time Data Pipelines
Alan Ngai and Premal Shah discuss best practices on monitoring distributed real-time data processing frameworks and how DevOps can gain control and visibility over these data pipelines.
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Creating Customer-Centric Products Using Big Data
Kriti Sharma talks about how Barclays is solving some of the toughest big data challenges in financial services using scalable, open source technology.
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Solving Business Problems with Data Science
The panelists discuss some of the unique problems that only data science can solve, the pitfalls and the success rate of data science projects.
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Hybrid Artificial Intelligence
Manuel Ebert explores how hybrid AI works, its impact on businesses, using it in existing businesses, and what we can expect from hybrid artificial intelligence in the years to come.
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Server-Less Design Patterns for the Enterprise with AWS Lambda
Tim Wagner defines server-less computing, examines the key trends and innovative ideas behind the technology, and looks at design patterns for big data, event processing, and mobile using AWS Lambda.
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Vowpal Wabbit, A Machine Learning System
John Langford discusses how to use Vowpal Wabbit in and as a machine learning system including architecture, unique capabilities, and applications, applied to personalized news recommendation.
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Large-Scale Stream Processing with Apache Kafka
Neha Narkhede explains how Apache Kafka was designed to support capturing and processing distributed data streams by building up the basic primitives needed for a stream processing system.
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Online Data Mining and Machine Learning
Edo Liberty presents some basic concepts and an introduction to the subfields of machine learning and data mining.
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