💡 Predict diabetes risk using machine learning by analyzing medical history and demographic data, aiding healthcare professionals in patient assessment.

🔍 Validate AI-generated content accuracy in fintech and compliance, ensuring safer information by checking claims against verified knowledge bases.

Optimize AI & Maximize ROI of your LLM tasks. Evaluates current state and recommends optimizations.

Multi-class confusion matrix library in Python

Fast emulated quadruple precision in Rust

Data quality estimations for OpenStreetMap

The Cerebros package is an ultra-precise Neural Architecture Search (NAS) / AutoML that is intended to much more closely mimic biological neurons than conventional neural network architecture strategies.

Script for calculating the optimal cut-off for max. F1-score, etc.

解决JavaScript与Node.js精度计算（浮点数计算精度）问题。支持数字、小数、字符串、数组、矩阵和表达式。Accurate is an precision calculation for JavaScript and Nodejs. supports numbers, decimals, strings, arrays, matrices and expression.

Using Logistic regression algorithm for predicting whether the patient has heart disease or not.

解决JavaScript与Node.js精度计算（小数、浮点数计算精度）问题，轻量级、性能较高。An lightweight and High performance precision calculation for JavaScript and Node.js.

Numbers with precision and a unit for JavaScript

This project aims to predict the success of mobile applications on the Google Play Store using machine learning. By analyzing various features such as app category, rating, number of installs, size, type (free or paid), and content rating, the model can classify whether an app is likely to be successful or not.

Deploy once. Continuously improve your AI agents in production.

extended precision math, accurate and performant

When it comes to implementing Responsible AI, there's no one-size-fits-all framework.

Accuracy Bounds

Projeto de Regressão Logística desenvolvido em Python com Google Colab Jupyter Notebook

Football Player and Element Detection with Deep Learning. This project implements and fine-tunes deep learning models to detect football players, referees, and the ball, and classify teams from Veo Cam 2 footage. YOLOv5, Faster R-CNN (ResNet-50), and VGG16 are compared for accuracy, speed, and practical deployment.

Ultra‑precise Windows time sync tray app with smart NTP selection, elegant UI, accurate multi‑sample ping, and optional IP‑aware timezone/region.