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머신러닝 · GitHub

모델 학습, 평가, 추론 프레임워크를 찾고 커뮤니티의 관심도를 비교하세요.

유용한 GitHub 프로젝트

4,740 프로젝트
1,116스타+2in 24h

Machine Learning projects with source code - Machine Learning projects for beginners, ML projects for final year college students, machine learning projects - beginner to advanced

mlops-zoomcamp

DataTalksClub

15,547스타+2in 24h
mlops-zoomcamp preview

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

머신러닝Jupyter NotebookGitHub

fun-rec

datawhalechina

7,484스타+2in 24h
fun-rec preview

추천 시스템 입문 튜토리얼입니다. 온라인에서 읽기: https://datawhalechina.github.io/fun-rec/

llm-algo-leetcode

datawhalechina

748스타+2in 24h
llm-algo-leetcode preview

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.
머신러닝Jupyter NotebookGitHub

deepinv

deepinv

850스타+2in 24h

DeepInverse: a PyTorch library for solving imaging inverse problems using deep learning

머신러닝PythonBSD-3-ClauseGitHub

spleeter

deezer

28,527스타+2in 24h

사전 학습된 모델을 포함한 Deezer 음원 분리 라이브러리.

1,501스타+2in 24h
Chatterbox-TTS-Server preview

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).

awesome-aws

donnemartin

14,197스타+2in 24h
awesome-aws preview

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

sonar

dphnAI

1,912스타+2in 24h
sonar preview

Large-scale LLM inference engine

  • Continuous batching and paged KV-cache management
  • Prefix caching enabled by default
머신러닝PythonAGPL-3.0GitHub
28,883스타+2in 24h
linkedin-skill-assessments-quizzes preview

LinkedIn 스킬 평가 2024년 답변 전체 참고 자료(aws-lambda, rest-api, javascript, react, git, html, jquery, mongodb, java, Go, python, machine-learning, power-point)로, LinkedIn Excel 테스트 풀이, LinkedIn 머신러닝 테스트, LinkedIn 테스트 문제와 답변을 포함합니다

머신러닝PythonAGPL-3.0GitHub

EEGDash

eegdash

92스타+2in 24h
EEGDash preview

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

머신러닝PythonBSD-3-ClauseGitHub

EliteQuant

EliteQuant

4,273스타+2in 24h

퀀트 모델링, 트레이딩 및 포트폴리오 관리 관련 온라인 리소스 목록

fly-brain

eonsystemspbc

1,031스타+2in 24h

초파리 뇌 에뮬레이션: Brian2, Brian2CUDA, PyTorch, NEST GPU 및 뉴로모픽 칩

머신러닝PythonGPL-2.0GitHub

caire

esimov

10,893스타+2in 24h
caire preview

콘텐츠를 인식해 이미지 크기를 조절하는 라이브러리

  • GUI progress indicator
  • Customizable command line support

MVision

Ewenwan

8,771스타+2in 24h
MVision preview

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

dinov3

facebookresearch

11,728스타+2in 24h
dinov3 preview

Reference PyTorch implementation and models for DINOv3

머신러닝Jupyter NotebookGitHub

jepa

facebookresearch

4,197스타+2in 24h
jepa preview

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

SUPIR

Fanghua-Yu

5,699스타+2in 24h
SUPIR preview

SUPIR는 실제 환경에서 사실적인 이미지 복원을 구현하기 위한 실용적인 알고리즘 개발을 목표로 합니다. 새로운 온라인 데모도 suppixel.ai에서 공개했습니다.

spikingjelly

fangwei123456

2,186스타+2in 24h

SpikingJelly is an open-source deep learning framework for Spiking Neural Network (SNN) based on PyTorch.

  • SNN modeling - Activation-based SNN components: spiking neurons, surrogate gradients, stateful and stateless modules. Predefined SNN models.
  • Training workflows - PyTorch-native training flows, online-learning utilities, and ANN2SNN conversion
머신러닝PythonApache-2.0GitHub