InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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Breakthroughs and the Future of (Deep) Reinforcement Learning
Andreas Bühlmeier discusses the foundation of Reinforced Learning and demonstrates how it is implemented. Also, he shows how to track and understand a system’s learning progress.
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ML's Hidden Tasks: A Checklist for Developers When Building ML Systems
Jade Abbott discusses the set of unexpected things that go on the "take it to production" checklist in the case of machine learning, and what are the tools that can help.
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CI/CD for Machine Learning
Sasha Rosenbaum shows how a CI/CD pipeline for Machine Learning can greatly improve both productivity and reliability.
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Machine Learning 101
Grishma Jena gives an overview of ML and delves deep into the pipeline used - right from fetching the data, the tools and frameworks used to creating models, gaining insights and telling a story.
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ML in the Browser: Interactive Experiences with Tensorflow.js
Victor Dibia provides a friendly introduction to machine learning, covers concrete steps on how front-end developers can create their own ML models and deploy them as part of web applications.
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Practical Change Data Streaming Use Cases with Apache Kafka & Debezium
Gunnar Morling discusses practical matters, best practices for running Debezium in production on and off Kubernetes, and the many use cases enabled by Kafka Connect's single message transformations.
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When Machine Learning Can't Replace the Human
Pamela Gay explores how creative software solutions let scientists explore the solar system.
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Future of Data Engineering
Chris Riccomini talks about the current state-of-the-art in data pipelines & data warehousing, and shares some of the solutions to current problems dealing with data streaming & warehousing.
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Rethinking Blockchain Contract Development
Manuel Chakravarty discusses how IOHK’s Plutus combines programming language theory, functional programming in Haskell, and theorem-proving in Agda to develop a new approach to blockchain contracts.
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Untangling the Mysteries of Qubits
Roy van Rijn explains how larger quantum algorithms work by explaining the quantum benefits in Shor's Prime Factoring algorithm.
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Big Data's Ethical Drought: The Thirst for More Data Has Led to a Lapse in Ethics and Privacy
Katharine Jarmul provides examples of data (mis)use and asking how we can work with data without violating the trust and privacy of users, producing an ethical product?
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Real-Time Stream Analysis in Functional Reactive Programming
Riccardo Terrell discusses about a reactive approach to application design, and how to account for handling events in near real time employing the Functional Reactive Programming paradigm.
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