InTDS ArchivebyJacob PieniazekDouble Machine Learning, Simplified: Part 1 — Basic Causal Inference ApplicationsLearn how to utilize DML in causal inference tasksJul 12, 20231363Jul 12, 20231363
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Heinrich KögelCausal Machine Learning in MarketingThis article provides a case study that demonstrates how we can leverage causal machine learning for better decision-making in marketing.Jul 31, 202372216Jul 31, 202372216
InTDS ArchivebySamuele MazzantiUsing Causal ML Instead of A/B TestingIn complex environments, Causal ML is a powerful tool because it is more flexible than A/B Testing, and it doesn’t require strong…Nov 29, 20221.6K17Nov 29, 20221.6K17
InTDS ArchivebyHarrison HoffmanCausal Machine Learning: What Can We Accomplish with a Single Theorem?Exploring and exploiting the seemingly innocent theorem behind Double Machine LearningMar 30, 20244962Mar 30, 20244962
InTDS ArchivebyAri Joury, PhDPropensity-Score Matching Is the Bedrock of Causal InferenceAnd how to get started with it using PythonDec 22, 20242102Dec 22, 20242102
Ari Joury, PhDUnderstanding The “Why”: 10 Techniques for Causal InferenceWith the right tools you can get some pretty deep insightsDec 23, 20244785Dec 23, 20244785
InCausal Data Sciencebyadam kelleherCausal Data ScienceI started a series of posts aimed at helping people learn about causality in data science (and science in general), and wanted to compile…Aug 12, 20161.5K2Aug 12, 20161.5K2
Alex KC4th Place Solution — $100k Causal Discovery Challenge — ADIA Lab x CrunchDAOBelow I detail my solution that earned a 4th place position in the Causal Discovery Challenge with a multiclass balanced accuracy across…Nov 22, 202471Nov 22, 202471
InTDS ArchivebyAleksander MolakJane the Discoverer: Enhancing Causal Discovery with Large Language Models (Causal Python)A practical guideline to LLM-enhanced causal discovery that minimizes the risks of hallucinations (with Python code)Oct 22, 20232723Oct 22, 20232723
InTowards AIbyAndrea BerdondiniA Modern Approach To The Fundamental Problem of Causal InferenceABSTRACT: The fundamental problem of causal inference defines the impossibility of associating a causal link to a correlation, in other…Nov 14, 20247001Nov 14, 20247001
InTDS ArchivebyShaw TalebiCausal Effects via the Do-operatorTranslating observations into interventionsSep 28, 20221673Sep 28, 20221673
InCausality in Data SciencebyKenneth StyppaIntroducing Causal Feature LearningCausal Feature Learning Pt. 1Oct 22, 2024961Oct 22, 2024961
Causal Wizard appOnline Causal Diagram (and DAG) drawing / editing toolsContentsJul 2, 2023342Jul 2, 2023342
MicropredictionA New Way to Detect Causality in Time-Series: Interview with Alejandro Rodriguez DominguezI virtually sat down with Alejandro Rodriguez Dominguez to discuss his recent paper with Om Hari Yadav on causality detection. I’m always…Nov 1, 20242123Nov 1, 20242123
InTDS ArchivebyShuyang XiangCausal SHAP values: A possible improvement of SHAP valuesAn introduction and a case studySep 2, 2022120Sep 2, 2022120
InTDS ArchivebySamuele MazzantiCausality in ML Models: Introducing Monotonic ConstraintsMonotonic constraints are key to making machine learning models actionable, yet they are still quite unusedSep 6, 20241.4K13Sep 6, 20241.4K13
InTDS ArchivebyRyan O'SullivanUsing Causal Graphs to answer causal questionsCausal AI, exploring the integration of causal reasoning into machine learningJan 31, 20246667Jan 31, 20246667
InTDS ArchivebyErdogan TaskesenAn Extensive Starters Guide For Causal Discovery using Bayesian ModelingBayesian approaches are becoming increasingly popular but can be overwhelming at the startOct 19, 20247455Oct 19, 20247455
InTDS ArchivebyMatteo CourthoudMean vs Median Causal EffectAn introduction to quantile regression in A/B testsOct 10, 20224392Oct 10, 20224392