Stars
Dataframes powered by a multithreaded, vectorized query engine, written in Rust
An index of algorithms for learning causality with data
Codebase for "Demystifying Black-box Models with Symbolic Metamodels", NeurIPS 2019.
Python code for training fair logistic regression classifiers.
Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.
Paper Augmented Reality Toolkit - interactive projection for Processing
Documentation for MIT CityScope Project
A 5e D&D encounter simulator written for my own amusement to test some hypotheses.
Inference in instrumental variables models robust to many instruments
Fit interpretable models. Explain blackbox machine learning.
A game theoretic approach to explain the output of any machine learning model.
A library for debugging/inspecting machine learning classifiers and explaining their predictions
Python Data Science Handbook: full text in Jupyter Notebooks
Code for reco-gym: A Reinforcement Learning Environment for the problem of Product Recommendation in Online Advertising
Code to run submissions for the Atlantic Causal Inference Competition
Notes and simulations on graduate level causal inference in statistics with applications to social sciences.
The winning solution to the Ad Placement Challenge (NIPS'17 Causal Inference and Machine Learning Workshop)
Data derived from the Linked Births and Deaths Data (LBIDD); simulated pairs of treatment assignment and outcomes; scoring code
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
Some notes on Causal Inference, with examples in python