Publications by R on Just be-cause
Better A/B testing with survival analysis
Pic by author – using DALL-E 3 When running experiments don’t forget to bring your survival kit I’ve already made the case in several blog posts (part 1, part 2, part 3) that using survival analysis can improve churn prediction. In this blog post I’ll show another use case where survival analysis can improve on common practices: A/B testing...
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“Correlation does not imply causation”. So what does?
Machine learning applications have been growing in volume and scope rapidly over the last few years. What’s Causal inference, how is it different than plain good ole’ ML and when should you consider using it? In this report I try giving a short and concrete answer by using an example. A typical data science task Imagine we’re tasked by the...
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“Correlation is not causation”. So what is?
Intro Machine learning applications have been growing in volume and scope rapidly over the last few years. What’s Causal inference, how is it different than plain good ole’ ML and when should you consider using it? In this report I try giving a short and concrete answer by using an example. A typical data science task Imagine we’re tasked ...
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“X affects Y”. What does that even mean?
On my last post I gave an intuitive demonstration of what’s causal inference and how it’s different than classic ML. After receiving some feedback I realize that while the post was easy to digest, some confusion remains. In this post I’ll delve a bit deeper into what the “causal” in Causal Inference actually means. Analyzing the effect...
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“X affects Y”. What does that even mean?
On my last post I gave an intuitive demonstration of what’s causal inference and how it’s different than classic ML. After receiving some feedback I realize that while the post was easy to digest, some confusion remains. In this post I’ll delve a bit deeper into what the “causal” in Causal Inference actually means. Analyzing the effect...
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Causal inference bake off (Kaggle style!)
Intro On my last few posts I’ve tried answering high level questions such as “What is Causal inference?”, “How is it different than ML?” and “When should I use it?”. In this post we finally get our hands dirty with some Kaggle style Causal Inference algorithms bake off! In this competition I’ll pit some well known ML algorithms vs...
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Causal inference bake off (Kaggle style!)
Intro On my last few posts I’ve tried answering high level questions such as “What is Causal inference?”, “How is it different than ML?” and “When should I use it?”. In this post we finally get our hands dirty with some Kaggle style Causal Inference algorithms bake off! In this competition I’ll pit some well known ML algorithms vs...
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My 2 cents on the “R vs Python” squabble
Intro In this post I’ll make an exception and instead of sharing my research I’ll chime in on the never ending “R vs Python” squabble. The tl;dr version is: R is superior to Python for doing data science If you’re a newcomer to data science you should probably learn Python. OK, so “what is data science” is probably the title of ev...
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My 2 cents on the “R vs Python” squabble
Intro In this post I’ll make an exception and instead of sharing my research I’ll chime in on the never ending “R vs Python” squabble. The tl;dr version is: R is superior to Python for doing data science If you’re a newcomer to data science you should probably learn Python. OK, so “what is data science” is probably the title of ev...
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“Real life” DAG simulation using the simMixedDAG package
Intro I’ve discussed on several blog posts how Causal Inference involves making inference about unobserved quantities and distributions (e.g. we never observe \(Y|do(x)\)). That means we can’t benchmark different algorithms on Causal Inference tasks (e.g \(ATE/CATE\) estimation) the same way we do in ML because we don’t have any ground tru...
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