DeekshaD / causalML-lecturenotesLinks
Lecture notes for the Causality in Machine Learning course
☆15Updated 6 years ago
Alternatives and similar repositories for causalML-lecturenotes
Users that are interested in causalML-lecturenotes are comparing it to the libraries listed below
Sorting:
- Working repository for Causal Tree and extensions☆446Updated 5 months ago
- Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflo…☆336Updated 10 months ago
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML☆777Updated 2 months ago
- Documentation and User Guide for DoubleML - Double Machine Learning in Python & R☆24Updated last month
- Causal Inference in Python☆573Updated 2 months ago
- A causal tree method (Causal Tree Learn (CTL)) for heterogeneous treatment effects in Python☆65Updated last year
- Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins☆1,319Updated 3 years ago
- Must-read papers and resources related to causal inference and machine (deep) learning☆737Updated 2 years ago
- DoubleML - Double Machine Learning in Python☆646Updated last week
- Repository with code and slides for a tutorial on causal inference.☆579Updated 5 years ago
- Generalized Random Forests☆1,042Updated last month
- Materials Collection for Causal Inference☆47Updated 2 years ago
- A data index for learning causality.☆476Updated last year
- ☆237Updated 2 years ago
- A Python package for causal inference using Synthetic Controls☆190Updated last year
- A Python package for modular causal inference analysis and model evaluations☆786Updated 5 months ago
- A curated list of causal inference libraries, resources, and applications.☆1,052Updated 5 months ago
- Resources related to causality☆267Updated last year
- Causal Inference Crash Course for Scientists - contains slides and Jupyter notebooks☆104Updated 4 months ago
- A version of scikit-learn that includes implementations of Wager & Athey and Scott Powers causal forests.☆22Updated 8 years ago
- Implementation of Deep IV: A Flexible Approach for Counterfactual Prediction☆157Updated 4 years ago
- Code for the Book Causal Inference in Python☆335Updated last year
- ☆104Updated 4 years ago
- Some notes on Causal Inference, with examples in python☆154Updated 5 years ago
- Sklearn-style implementations of Neural Network-based Conditional Average Treatment Effect (CATE) Estimators.☆147Updated last year
- CausalLift: Python package for causality-based Uplift Modeling in real-world business☆350Updated 2 years ago
- EconML/CausalML KDD 2021 Tutorial☆162Updated 2 years ago
- Synthetic difference in differences☆285Updated last year
- Counterfactual Regression☆313Updated 2 years ago
- Code accompanying the paper "Empirical analysis of model selection for heterogeneous causal effect estimation"☆13Updated 7 months ago