Repository History
32 repositories tagged with machine-learning
Evidently: Open-Source ML and LLM Observability Framework
Evidently is an open-source Python library designed for evaluating, testing, and monitoring machine learning and large language model systems. It provides over 100 built-in metrics for various tasks, from data drift detection to LLM judges, supporting both tabular and text data. This framework helps ensure the quality and performance of AI-powered systems throughout their lifecycle.
MarkLLM: An Open-Source Toolkit for LLM Watermarking
MarkLLM is an open-source toolkit designed to simplify the research and application of watermarking technologies for large language models (LLMs). It offers a unified framework for implementing various watermarking algorithms, alongside robust visualization and comprehensive evaluation tools. This toolkit helps researchers and the broader community understand and assess the authenticity and origin of machine-generated text.
bg-remove: Client-Side Image Background Removal with Transformers.js
bg-remove is a powerful React + Vite application that enables free, client-side image background removal directly in your browser. Leveraging machine learning models via Transformers.js, it ensures all processing happens locally, prioritizing user privacy. This tool offers one-click removal, custom background options, and optional WebGPU acceleration for enhanced performance.
NVIDIA PhysicsNeMo: Deep Learning Framework for Physics-ML Models
NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building, training, and fine-tuning Physics AI models. It leverages state-of-the-art scientific machine learning methods, enabling real-time predictions by combining physics knowledge with data. This framework provides scalable, GPU-optimized tools for AI4Science and engineering applications.
TensorRec: A TensorFlow Recommendation Framework in Python
TensorRec is a Python recommendation system built on TensorFlow, designed for quickly developing and customizing recommendation algorithms. It allows users to define custom representation and loss functions while handling data manipulation, scoring, and ranking. Although not under active development, it provides a solid foundation for understanding and implementing recommender systems.
pyAudioAnalysis: A Python Library for Audio Feature Extraction and Analysis
pyAudioAnalysis is an open-source Python library designed for a wide range of audio analysis tasks. It provides robust functionalities for feature extraction, classification, and segmentation of audio data, making it a valuable tool for researchers and developers. This library simplifies complex audio signal processing and machine learning applications.
Roboflow Notebooks: Master State-of-the-Art Computer Vision Models
Roboflow Notebooks offers a comprehensive collection of tutorials designed to help users master state-of-the-art computer vision models and techniques. This repository covers a wide range of topics, from foundational architectures like ResNet to cutting-edge models such as RF-DETR, YOLO11, SAM 3, and Qwen3-VL. It serves as an invaluable resource for anyone looking to explore and implement advanced computer vision solutions.
agent-service-toolkit: A Comprehensive Toolkit for AI Agent Services with LangGraph
The agent-service-toolkit is a full-featured repository for building and running AI agent services. It leverages LangGraph for sophisticated agent logic, FastAPI for a robust service API, and Streamlit for an interactive chat interface. This toolkit provides a comprehensive and robust template for developing and deploying custom AI agents with ease.
PaddleOCR: A Powerful OCR Toolkit for Structured Document Data
PaddleOCR is an industry-leading, production-ready OCR and document AI engine that transforms any PDF or image document into structured, AI-friendly data. It offers end-to-end solutions from text extraction to intelligent document understanding, supporting over 100 languages with high accuracy and efficiency.
ML-From-Scratch: Machine Learning Models and Algorithms in NumPy
ML-From-Scratch is a comprehensive GitHub repository offering bare-bones NumPy implementations of fundamental machine learning models and algorithms. It emphasizes accessibility, making complex concepts easier to understand for learners and practitioners. This project covers a wide range of topics, from linear regression to deep learning and reinforcement learning, all implemented from scratch.
Spotlight: Deep Recommender Models with PyTorch
Spotlight is a Python library built on PyTorch for developing deep and shallow recommender models. It offers a comprehensive set of building blocks for various loss functions, representations, and utilities for handling recommendation datasets. This tool is designed for rapid exploration and prototyping of new recommender systems.
Fast Music Remover: Lightweight Music and Noise Removal for Media
Fast Music Remover is a C++ based, lightweight tool designed for efficient music and noise removal from YouTube and other internet media. It leverages DeepFilterNet for advanced audio enhancement, empowering users to take control of their media consumption. The project offers a modular, cross-platform solution with both a web UI and containerized deployment options.