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Data science tutorial: causal inference model selection | Jonathan Hershaff

Data science tutorial: causal inference model selection | Jonathan Hershaff

Like hyper-parameter tuning, model selection techniques are commonplace in machine learning but often overlooked in the causal inference space. I've sat in plenty of seminars with data scientists who had a time series and a limited set of treated units who chose a model and went with it without testing alternatives. This can have important ...

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Causal Inference Tutorial

New approaches for causal inference from genomic data

New approaches for causal inference from genomic data

UNICEF webinar: Overview: strategies for causal inference - Resource

UNICEF webinar: Overview: strategies for causal inference - Resource

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Foundations of causal inference and its impacts on machine learning webinar

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Lecture 14: Causal Inference, Part 1 | Machine Learning for Healthcare | Electrical Engineering and Computer Science | MIT OpenCourseWare

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