Aprendizaje automático · GitHub

100+ AI Machine learning Deep learning Computer vision NLP Projects with code

Free MLOps course from DataTalks.Club. Register here 👇🏼 to get notified about the next cohort

Tutorial introductorio sobre sistemas de recomendación. Léelo en línea: https://datawhalechina.github.io/fun-rec/

LLM algorithm practice lab with theory, solutions, and test cases.《大模型算法与系统教程》面向大模型入门到进阶的算法实战教程，覆盖原理讲解、答案解析、测试用例与 CUDA/Triton 实战。

• Notebook-first: Each lesson is organized around runnable code, exercises, answer cells, and basic validation.
• Goal-oriented entry: Start from Part 02 for implementation practice, or follow the architecture, post-training, inference, performance, and operator routes.

Un repositorio para la IA documental

Self-host the powerful Chatterbox TTS model. This server offers a user-friendly Web UI, flexible API endpoints (incl. OpenAI compatible), predefined voices, voice cloning, and large audiobook-scale text processing. Runs accelerated on NVIDIA (CUDA), AMD (ROCm), and CPU.

• DGX Spark / sm_121 support via the new docker-compose-cu130.yml (CUDA 13.0, PyTorch 2.10). RTX 30/40/50 keep using cu121 / cu128.
• AMD Strix Halo support via docker-compose-strixhalo.yml (ROCm 7.2, HSA_OVERRIDE_GFX_VERSION=11.0.0).

A curated list of awesome Amazon Web Services (AWS) libraries, open source repos, guides, blogs, and other resources. Featuring the Fiery Meter of AWSome.

Large-scale LLM inference engine

• Continuous batching and paged KV-cache management
• Prefix caching enabled by default

Referencia completa de 2024 sobre las respuestas de las evaluaciones de aptitudes de LinkedIn (aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning y power-point), con soluciones para el test de Excel de LinkedIn, el test de machine learning de LinkedIn y preguntas y respuestas de los tests de LinkedIn

EEG-DaSh: an open data, tool, and compute resource. a Python library and catalog for 700+ BIDS-first EEG, MEG, fNIRS, EMG, and iEEG datasets, ML-ready via PyTorch

Biblioteca de redimensionado de imágenes según el contenido

• GUI progress indicator
• Customizable command line support

机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶

Reference PyTorch implementation and models for DINOv3

PyTorch code and models for V-JEPA self-supervised learning from video.

SUPIR tiene como objetivo desarrollar algoritmos prácticos para la restauración fotorrealista de imágenes en entornos reales. También hemos publicado una nueva demostración en línea en suppixel.ai.

FASHN VTON v1.5: Efficient Maskless Virtual Try-On in Pixel Space

La biblioteca de aprendizaje profundo fastai