InfoQ Homepage Machine Learning Content on InfoQ
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Continuous Optimization of Microservices Using ML
Ramki Ramakrishna shares Twitter’s recent experience in applying Bayesian optimization to the performance tuning problem, discussing a service used for continuously optimizing microservices.
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Automating Netflix ML Pipelines with Meson
Davis Shepherd and Eugen Cepoi discuss the evolution of ML automation at Netflix and how that lead them to build Meson, challenges faced and lessons learned automating thousands of ML pipelines.
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ML for Question and Answer Understanding @Quora
Nikhil Dandekar discusses how Quora extracts intelligence from questions using machine learning, including question-topic labeling, removing duplicate questions, ranking questions & answers, and more.
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Production Machine Learning
Jan Machacek discusses the challenges in writing deep learning code, testing and validating data management, environments, model storage & serving, validating data reporting, and CI&CD.
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The Joy of Stochastic Gradient Descent
Carin Meier takes a look at the joys of Deep Learning, discussing how Deep Learning is changing how people approach programming, communicate with each other, and even what it means to be human.
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AI in Finance: from Hype to Marketing and Cybersec Applications
Natalino Busa illustrates a number of use cases of using AI and machine learning techniques in finance, such as transaction fraud prevention and credit authorization.
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Julia: A Modern Language for Modern ML
Simon Byrne and Viral Shah talk about Julia, a modern high-performance, dynamic language for technical computing, with many features which make it ideal for machine learning.
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Fighting Online Fraud and Abuse with Large-Scale Machine Learning at Sift Science
Jacob Burnim discusses Sift’s approach to building a ML system to detect fraud and abuse, including training models, handling imbalanced classes, sharing learning, measuring performance, etc..
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Systems That Learn
Stephen Buckley discusses the Systems That Learn initiative which aims to create systems that learn by combining expertise in Systems and Machine Learning.
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Primer on Neural Networks
Chase Aucoin introduces neural networks with examples and simple breakdowns about the math involved in a way accessible to a large audience.
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Online Learning & Custom Decision Services
Markus Cozowicz and John Langford talk about the new system they have created which automates exploit-explore strategies, data gathering, and learning to create useable online interactive learning.
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Machine Learning in Academia and Industry
Deborah Hanus discusses some of the challenges that can arise when working with data.
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