The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).
The concept of using a LLM for developing a work plan.
This repository aims to explore all possibilities available on Microsoft's DoWhy package, based on the Causal Inference Theory and Principles.
Causal Inference for Marketplace
Internship Project on Causal Inference (The causal effect of multi-level treatment of intervention using observational data).
IISc/CSA E0-294: Systems for Machine learning - Course project on employing causal insights in DNN model pruning and performance
Bayesian Causal Inference in Doubly Gaussian DAG-probit Models
📊 Causal Analysis of Remote Work Impact on Employee Productivity A comprehensive statistical analysis demonstrating a 7.14-point increase in employee productivity with remote work arrangements. Uses DoWhy framework and propensity score matching to establish causation beyond correlation. 🔍 Key Features: - Causal inference analysis - DoWhy
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