Why we standardise using training statistics when doing Machine Learning
This post runs through why it’s important to preprocess new data that you’re passing to a Machine Learning model using statistics calculated from the training data.
R
Introducing group sequential designs for early stopping of A/B tests
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Simulating A/B tests with data.table
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Adjusting for covariates and baseline differences in A/B testing
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Approximate Nearest Neighbours in R and Spark
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Feature selection by cross-validation with sparklyr
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Cross-validation with sparklyr 2: Electric Boogaloo
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SparkR vs sparklyr for interacting with Spark from R
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Machine learning and k-fold cross validation with sparklyr
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Writing your thesis with bookdown
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