Failure Probability Modeling: A Practical Framework for Distributed Reliability
A practical guide (with examples) to using statistical modeling to understand, predict, and prevent mysterious failures in modern distributed systems.
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Stats, experiments, and AI superpowers for engineers
Start with the core thesis, then go deeper into individual concepts: probability, sampling, hypothesis testing, power, Bayesian thinking, and more — always from a software engineer's point of view.
Eight Short Stories About Engineers Who Quietly Save the Day With Statistics
Most software engineers spend years sharpening their coding skills but go surprisingly far without understanding the statistical forces shaping their systems. Here are eight stories of engineers solving real problems with stats.
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