OCEAN: Optimal Counterfactual Explanations in Tree Ensembles (ICML 2021)

Generate Diverse Counterfactual Explanations for any machine learning model.

Active Bayesian Causal Inference (Neurips'22)

Código Python, Jupyter Notebooks, archivos csv con ejemplos para los ejercicios del Blog aprendemachinelearning.com y del libro Aprende Machine Learning en Español

A PyTorch-based End-to-End Predict-then-Optimize Library for Linear and Integer Programming

Causal Inference and Discovery in Python by Packt Publishing

A curated list of Quarto talks, tools, examples & articles! Contributions welcome!

Causal Inference 1 Mixtape Session taught by Scott Cunningham

Implement the optimal classification trees algorithm published by MIT researchers

Aquí se encuentran los códigos asociados al producto "Algoritmo de Categorización" del proyecto COVID1006, financiado a través del Concurso Asignación Rápida ANID. Dentro del proyecto se implementa…

JuliaCon 2022 - Introduction to Julia Tutorial

Course material for 1RT700 Statistical Machine Learning

#TidyTuesday submissions

"Probabilistic Machine Learning" - a book series by Kevin Murphy

"Probabilistic Machine Learning" - a book series by Kevin Murphy

Proyecto de tesis que analiza una base de datos para aplicar LDA jerarquizado

Natural Language Processing

Material del curso de Deep Learning de la Universidad de Chile

Python code for "Probabilistic Machine learning" book by Kevin Murphy

An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code

JuliaLang version of "An Introduction to Statistical Learning: With Applications in R"

Codes for the book "Julia Programming for Operations Research"

Material del curso de Sistemas Recomendadores IIC3633 PUC Chile

Statistical Rethinking course at MPI-EVA from Dec 2018 through Feb 2019

Market Analysis Course with Interactive RTutor Problemsets, Videos and Quizzes