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Counting is Hard: Probabilistic Algorithms for View Counting at Reddit
Krishnan Chandra explains the challenges of building a view counting system at scale, and how Reddit used probabilistic counting algorithms to make scaling easier.
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Developing Data and ML Pipelines at Stitch Fix
Jeff Magnusson discusses thoughts and guidelines on how Stitch Fix develops, schedules, and maintains their data and ML pipelines.
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Counterfactual Evaluation of Machine Learning Models
Michael Manapat discusses how Stripe evaluates and trains their machine learning models to fight fraud.
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Machine Learning Pipeline for Real-Time Forecasting @Uber Marketplace
Chong Sun and Danny Yuan discuss how Uber is using ML to improve their forecasting models, the architecture of their ML platform, and lessons learned running it in production.
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