Repositories (7)
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).
Slides, paper notes, class notes, blog posts, and research on ML 📉, statistics 📊, and AI 🤖.
Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.
Interpret text data using LLMs (scikit-learn compatible).
Generating paper titles (and more!) with GPT trained on data scraped from arXiv.
Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)
News Balancer takes a story and provides articles on that story with credibility and varying political bias. The homepage will randomly generate a story from its archives, but a user can type in a query to get stories relating to their query along with their credibility / political bias.