André Cruz's repositories
bias-detection
Detection of propaganda or partisan allegiance in natural text.
feup-lpoo-armadillo
Project developed for 'Object Oriented Programming Laboratory', a second year subject @FEUP. Made in collaboration with @edgaracarneiro.
semeval2019-hyperpartisan-news
Our submission to the SemEval2019 shared task on Hyperpartisan News Detection.
python-proj-boilerplate
Boilerplate code and configurations for python projects
han-attention-plot
Plot of the attention in a HAN (Hierarchical Attention Networks)
NLP-progress
Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.
tum-contests
Repository for the Practical Course on Algorithms for Programming Contests @ TUM
advent-of-code-2023
My advent of code solutions for year 2023.
AIF360
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
AndreFCruz.github.io
My personal website (as of March 2023).
Awesome-LLM-Tabular
Awesome-LLM-Tabular: a curated list of Large Language Model applied to Tabular Data
doubleml-for-py
DoubleML - Double Machine Learning in Python
error-parity
Achieve error-rate fairness between societal groups for any score-based classifier.
fairgbm-fork
Train Gradient Boosting models that are both high-performance *and* Fair!
fairlearn
A Python package to assess and improve fairness of machine learning models.
feedzai-openml
API for Feedzai's Open Machine Learning that allows to integrate ML algorithms in Feedzai's platform.
feedzai-openml-java
Implementations for Feedzai's OpenML API
feup-ldso
Mobile app (ReactNative) + Administration web-site (React) for showcasing social-impact projects from U. Porto's Faculties. Backend is in Node.js + Loopback, and everything is Dockerized :whale:
folktables
Datasets derived from US census data
google-foobar
Google foo.bar coding challenge
lm-evaluation-harness
A framework for few-shot evaluation of language models.
surveying-language-models
Code to reproduce the paper "Questioning the Survey Responses of Large Language Models"
tableshift
A benchmark for distribution shift in tabular data
timeshap
TimeSHAP explains Recurrent Neural Network predictions.