CausalAIBook / MetricsMLNotebooksLinks
Notebooks for Applied Causal Inference Powered by ML and AI
☆138Updated 8 months ago
Alternatives and similar repositories for MetricsMLNotebooks
Users that are interested in MetricsMLNotebooks are comparing it to the libraries listed below
Sorting:
- Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks☆108Updated last week
- difference-in-differences in Python☆106Updated last year
- python implementation of Peng Ding's "First Course in Causal Inference"☆174Updated last year
- Machine Learning and Causal Inference taught by Brigham Frandsen☆218Updated last month
- ☆23Updated last year
- This material has been created based on the tutorials of the course 14.388 Inference on Causal and Structural Parameters Using ML and AI …☆17Updated 2 years ago
- This repository consolidates my teaching material for "Causal Machine Learning".☆260Updated last month
- JupyterNotebook for the MIT course☆16Updated 7 months ago
- Replication files for Chernozhukov, Newey, Quintas-Martínez and Syrgkanis (2021) "RieszNet and ForestRiesz: Automatic Debiased Machine Le…☆14Updated 3 years ago
- Official repository for the mcf package.☆22Updated this week
- Documentation and User Guide for DoubleML - Double Machine Learning in Python & R☆24Updated this week
- Lectures and Tutorials for the Causal AI course☆47Updated 3 weeks ago
- Packages of Example Data for The Effect☆150Updated last year
- Causal Inference in Python☆44Updated 2 months ago
- Lecture Notes on Statistical Inference☆77Updated last year
- Notes, exercises and other materials related to causal inference, causal discovery and causal ML.☆158Updated last month
- Synthetic difference in differences for Python☆85Updated last year
- Slides for the Seattle University Causal Inference Class☆143Updated 4 years ago
- Python implementation of the original R sensemakr package: https://github.com/carloscinelli/sensemakr☆54Updated 6 months ago
- This course is an overview of applied causal inference.☆52Updated 6 months ago
- Code associated with paper: Orthogonal Machine Learning for Demand Estimation: High-Dimensional Causal Inference in Dynamic Panels, Seme …☆27Updated 2 years ago
- CSDID☆35Updated 4 months ago
- This tutorial will introduce key concepts in machine learning-based causal inference. This tutorial is used by professor Susan Athey in t…☆14Updated 2 years ago
- Design of Simulations using WGAN☆55Updated 3 years ago
- Course Materials for AEA Short Course on Modern Sampling Methods☆29Updated 3 years ago
- This python package estimates dynamic panel data model using difference GMM and system GMM.☆31Updated 10 months ago
- Bayesian Causal Forests☆50Updated last year
- Material for the exercise sessions of master course Machine Learning for Economic Analysis @UZH☆86Updated 3 years ago
- A Python package for causal inference using Synthetic Controls☆193Updated last year
- ☆14Updated 9 months ago