Large Scale benchmarking of state of the art text vectorizers
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Updated
Apr 18, 2026 - Python
Large Scale benchmarking of state of the art text vectorizers
Predicts antibiotic resistance rates for bacteria–antibiotic pairs from biological resistance mechanisms, using a GradientBoosting model trained on ATLAS clinical surveillance data. Includes an interactive Streamlit lab for exploring predictions.
apply machine learning algorithm, such as regression, tree methods, as well as a series of feature engineering to predict housing price
Ensemble_classification
Classroom-PeopleCounting.
PrefRank predicts which LLM response humans prefer using a 3-class classification framework. Combines linguistic, structural, and TF-IDF features with calibrated models (MLP, RF, XGBoost, LightGBM) — no embeddings required.
Interactive geospatial machine learning application for visualizing and predicting shark habitat suitability using NASA satellite data.
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