Causal Inference
Explore recommended reads, summarized by AI
Causal Graphs and Structure
Approaches using directed acyclic graphs and knowledge graphs to represent and discover causal relationships.
Bayesian Causal Inference
Causal Graphs and DAGs
Causal Machine Learning
Techniques combining machine learning with causal inference for prediction and decision-making.
Deploying Causal ML Models
Double Machine Learning
Uplift Modeling
Experimental and Quasi-Experimental Methods
Approaches to estimating causal effects from experiments and observational data with natural variation.
A/B Testing Challenges
Difference-in-Differences
Synthetic Control Methods
Foundations and Methods
Introductions to core concepts, techniques, and debates in causal inference for data scientists.
Critiques of Correlation-Based Analysis
Getting Started with Causal Inference
Overviews of Causal Inference
Marketing and Business Applications
Applications of causal inference to marketing attribution, budget optimization, and customer strategy.
