CAUSAL INFERENCE

This repository aims to explore all possibilities available on Microsoft's DoWhy package, based on the Causal Inference Theory and Principles.

The concept of using a LLM for developing a work plan.

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

Internship Project on Causal Inference (The causal effect of multi-level treatment of intervention using observational data).

CzechFOI-SIM

This project is a comprehensive data science initiative focused on improving the lives of animals in shelters. We aim to leverage advanced analytical methods to predict shelter animal outcomes and optimize resource allocation.

📊 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

MUMPS-max1D-or-2D

PERT-max1D-or-3D

CausalAnalysisDoWhyCounterFactualNetworks_FreemiumGameplayChurn_EngineeredSyntheticData

MMR-max1D-or-2D

MMR-EU-N-max1D-or-2D

Causal Inference for Marketplace

The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).

CzechFOI-MEAN

A Streamlit web application for discovering causal relationships in your data using Microsoft's DoWhy library. This tool helps you identify and quantify causal effects between variables in your datasets through correlation-based graph discovery and rigorous causal inference.

DoWhy/EconML toolkit for visualizing causal paths and estimating treatment effects