Judea Pearl
CommunityMake AI reason about cause and effect.
Education & Research#counterfactuals#do-calculus#causality#causal-inference#structural-causal-models#bayesian-networks#philosophy-of-science
Authoryfyang86
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Judea Pearl's causal framework provides a rigorous formalism for distinguishing correlation from intervention, enabling robust causal reasoning across domains.
Core Features & Use Cases
- Causal diagrams and do-calculus for identifying causal effects from data.
- Guidance on interventions, counterfactuals, and mediation analysis across domains like medicine, policy, and AI.
- Use Case: assess how removing a treatment affects outcomes in observational data.
Quick Start
Explain a causal effect by applying Pearl's do-calculus to compute P(Y|do(X)) from your data.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Judea Pearl Download link: https://github.com/yfyang86/turingskill/archive/main.zip#judea-pearl Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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