A developer found that improving data quality through feature engineering boosted a Logistic Regression model's accuracy from 72% to 86%—a 14-percentage-point gain—without changing the algorithm. By h…
A developer built TrustGuard AI, a fraud detection system that catches 99.76% of fraudulent transactions on the PaySim dataset, achieving an AUC-ROC of 0.9995 and Recall of 0.9976 on a 6.3 million row…
An arXiv preprint (arXiv:2606.03995) reports an explainable machine learning model that achieved near-perfect three-class classification of Alzheimer's disease, mild cognitive impairment, and normal c…
Researchers developed an XGBoost machine learning model using eight routine clinical features from the Alzheimer's Disease Neuroimaging Initiative dataset that achieved 94.3% accuracy and a 0.982 macr…
A developer built Sentinel, a real-time fraud detection system that processes 71,000 requests per second with p95 latency under 6 milliseconds. The system handles 7.8 million requests with zero errors…
A developer benchmarked four lightweight transformer models—DistilBERT, MobileBERT, TinyBERT-6L, and TinyBERT-4L—against traditional ML baselines for fault detection, finding that TinyBERT-4L achieved…
A developer rebuilt Project Haven, an offline-first bushfire response platform, integrating Hermes Agent as the core AI engine for emergency guidance, scheduled fire-risk briefings, and recovery grant…
Swiggy developed a real-time machine learning ranking system for search autocomplete that replaces hand-tuned heuristics with a learned ranking model running directly inside OpenSearch, operating unde…