InfoQ Homepage QCon Software Development Conference Content on InfoQ
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Federated Learning: Rewards & Challenges of Distributed Private ML
Eric Tramel discusses the basic concepts underlying the federated ML approach, the advantages it brings, as well as the challenges associated with constructing federated solutions.
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Michelangelo Palette: A Feature Engineering Platform at Uber
Amit Nene and Eric Chen discuss the infrastructure built by Uber for Michelangelo ML Platform that enables a general approach to Feature Engineering across diverse data systems.
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Instrumentation, Observability & Monitoring of Machine Learning Models
Josh Wills discusses the monitoring and visibility needs of machine learning models in order to bridge gaps between ML practitioners and DevOps.
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Habito: The Purely Functional Mortgage Broker
Will Jones talks about Haskell at Habito, some of the wins and trade-offs. He also talks about why functional programming is beneficial for large projects, and with migrating a data store.
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Balancing Risk and Psychological Safety
Andrea Dobson focuses on understanding the principles of the learning organizations, who can benefit, how to implement, and covers risks, pitfalls and effects of the learning organizational culture.
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The Future of Operating Systems on RISC-V
Alex Bradbury gives an overview of the status and development of RISC-V as it relates to modern operating systems, highlighting major research strands, controversies, and opportunities to get involved
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Privacy: The Last Stand for Fair Algorithms
Katharine Jarmul discusses research related to fair-and-private ML algorithms and privacy-preserving models, showing that caring about privacy can help ensure a better model overall and support ethics
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RxJS: A Better Way to Write Front-End Applications
Hannah Howard talks about the premise of functional reactive programming and how it represents a major conceptual shift but one that can vastly simplify front-end programming.
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The Future of Transportation
Anita Sengupta discusses the future of transportation with an eye towards how machine learning and AI will help shape the future.
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Massive Scale Anomaly Detection Framework
Guy Gerson introduces an anomaly detection framework PayPal uses, focusing on flexibility to support different types of statistical and ML models, and inspired by scikit-learn and Spark MLlib.
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Modern NLP for Pre-Modern Practitioners
Joel Grus discusses the latest in NLP research breakthrough, and how to incorporate NLP concepts and models into a project.
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Scaling for the Known Unknown
Suhail Patel explains how Monzo prepared for the recent crowdfunding which saw more than 9,000 people investing in the first 5 minutes and covers Monzo's microservice architecture (on Go & Kubernetes)
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