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causality, computing, & coffee
causality, computing, & coffee

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@tlverse @CoVPN @nshlab @ictml-project

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nhejazi/README.md

hey there, i'm nima

i'm an academic (bio)statistician working at the interface of causal inference, machine learning, semi-parametric statistics, and computational statistics. i'm passionate about building accessible open-source software for model-agnostic and assumption-lean statistical and causal machine learning methods, and i'm most easily excited by problems at the interface of statistics and the biomedical and public health sciences.

are you looking for open source software for targeted causal machine learning? consider checking out the tlverse project and browsing our open source handbook!

nima's github stats

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  1. tlverse/sl3 tlverse/sl3 Public

    💪 🤔 Modern Super Learning with Machine Learning Pipelines

    R 99 40

  2. haldensify haldensify Public

    📦 R/haldensify: Highly Adaptive Lasso Conditional Density Estimation

    R 17 5

  3. tlverse/hal9001 tlverse/hal9001 Public

    🤠 📿 The Highly Adaptive Lasso

    R 49 15

  4. tlverse/tmle3shift tlverse/tmle3shift Public

    🎯 🎲 Targeted Learning of the Causal Effects of Stochastic Interventions

    R 16 1

  5. txshift txshift Public

    📦 🎲 R/txshift: Efficient Estimation of the Causal Effects of Stochastic Interventions, with Corrections for Outcome-Dependent Sampling

    R 13 4

  6. Netflix/sherlock Netflix/sherlock Public

    R package for causal machine learning for segment discovery and analysis

    R 30 4