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Maschinelles Lernen · GitHub

Finde Frameworks zum Trainieren, Bewerten und Ausführen von Modellen und vergleiche das Community-Interesse.

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7,345 Projekte

Numerics

USACE-RMC

34Sterne

Numerics is a free and open-source library for .NET developed by USACE-RMC, providing a comprehensive set of methods and algorithms for numerical computations and statistical analysis.

Maschinelles LernenC#0BSDGitHub

video_features

v-iashin

661Sterne
video_features preview

Extract video features from raw videos using multiple GPUs. We support RAFT flow frames as well as S3D, I3D, R(2+1)D, VGGish, CLIP, and TIMM models.

Maschinelles LernenPythonMITGitHub

synthcity

vanderschaarlab

696Sterne
synthcity preview

A library for generating and evaluating synthetic tabular data for privacy, fairness and data augmentation.

  • :key: Easy to extend pluginable architecture.
  • :cyclone: Several evaluation metrics for correctness and privacy.
Maschinelles LernenPythonApache-2.0GitHub

yolo-vision-pipeline-rknn

VaporTang

51Sterne

统一的 YOLOv8 视觉部署流水线。将模型训练、ONNX 导出与 RKNN 量化转换整合入单一代码库。支持 Win/WSL 跨平台一键部署，并提供专业的数据集管理与去重工具，轻松适配 RK3588/RK3568 等硬件

Maschinelles LernenPythonApache-2.0GitHub

Kinetic.jl

vavrines

150Sterne
Kinetic.jl preview

Universal modeling and simulation of fluid mechanics upon machine learning. From the Boltzmann equation, heading towards multiscale and multiphysics flows.

Maschinelles LernenJuliaMITGitHub

mpesa_safaricom-fraud_anomaly_detection

Victor-Kipruto-Rop

34Sterne

Real-time fraud detection engine for M-Pesa mobile money — Kafka/Flink streaming, ML-based risk scoring, and explainable multi-signal checks (velocity, SIM swap correlation, mule networks) feeding an interaction-aware decision engine, with a full production pipeline from ingestion through dbt analytics.

Maschinelles LernenPythonGitHub

Real-time-stock-market-prediction

victor369basu

647Sterne

In this repository, I have developed the entire server-side principal architecture for real-time stock market prediction with Machine Learning. I have used Tensorflow.js for constructing ml model architecture, and Kafka for real-time data streaming and pipelining.

Maschinelles LernenJavaScriptGitHub