InfoQ Homepage Machine Learning Content on InfoQ
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Rethinking Deep Learning: Neural Compute Stick
Darren Crews talks about the The Movidius Neural Compute Stick (NCS) - a tiny fanless deep learning device that one can use to learn AI programming at the edge.
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$200 Self-Driving Cars with RasPi and Tensorflow
William Roscoe and Adam Conway build and drive the $200 open source self driving Donkey Car and talk about about the hardware components & software that let it drive, capture data, create autopilots.
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Adding AI Smarts with Cognitive Services
Stephen Bohlen discusses Microsoft’s Cognitive Services, how to use them, exploring services for Facial Recognition, object detection, NLP, as well as Topic Extraction and Sentiment Analysis.
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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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Bias in BigData/AI and ML
Leslie Miley discusses how inherent bias in data sets has affected things from the 2016 Presidential race to criminal sentencing in the United States.
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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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