nyongja

nyongja's Stars

• torvalds/linux

  Linux kernel source tree

  Language:C179k53.3k

• antirez/rax

  A radix tree implementation in ANSI C

  Language:C1.1k162

• kubernetes/kubernetes

  Production-Grade Container Scheduling and Management

  Language:Go110k39.3k

• mitchellh/mapstructure

  Go library for decoding generic map values into native Go structures and vice versa.

  Language:Go7.9k670

• fatih/structs

  Utilities for Go structs

  Language:Go3.9k695

• redislabs-training/ru202

  Source code for the RU202 Redis Streams Course

  Language:HTML3729

• dranikpg/gtrs

  Turn Redis streams into typed Go channels in just a few lines

  Language:Go7712

• felipeagger/go-redis-streams

  Demo using messaging with Redis Streams in Golang

  Language:Go338

• twitter/the-algorithm

  Source code for Twitter's Recommendation Algorithm

  Language:Scala62.1k12.2k

• golang-standards/project-layout

  Standard Go Project Layout

  Language:Makefile48.5k5.1k

• wikibook/mlsdp

  《머신러닝 시스템 디자인 패턴》 예제 코드

  Language:Python6227

• labstack/echo

  High performance, minimalist Go web framework

  Language:Go29.5k2.2k

• nats-io/nats.py

  Python3 client for NATS

  Language:Python868177

• cynricfu/MAGNN

  Metapath Aggregated Graph Neural Network for Heterogeneous Graph Embedding

  Language:Python38868

• brave-people/brave-tech-interview

  🙋 핵심을 질문하다. 그리고 용감하게 대답하다. 국내 IT기업부터 실리콘밸리까지 "현직자가 해설해주는 기술면접"

  4k310

• xhcgit/LightGCN-implicit-DGL

  Language:Python253

• yoongi0428/RecSys_PyTorch

  PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.

  Language:Python13620

• gtshs2/Collaborative-Denoising-Auto-Encoder

  Collaborative Denoising Auto-Encoder for Top-N Recommender Systems (CDAE)

  Language:Python2612

• jinmang2/boostcamp_ai_tech_2

  :fire: Naver Boostcamp AI Tech 2기

  Language:Python474

• pytorch/torchrec

  Pytorch domain library for recommendation systems

  Language:Python1.9k406

• CoinCheung/pytorch-loss

  label-smooth, amsoftmax, partial-fc, focal-loss, triplet-loss, lovasz-softmax. Maybe useful

  Language:Python2.2k373

• google-deepmind/deepmind-research

  This repository contains implementations and illustrative code to accompany DeepMind publications

  Language:Jupyter Notebook13.1k2.6k

• ray-project/ray

  Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

  Language:Python33.1k5.6k

• RS-KR/GNN-RS-Beginner

  473

• boostcampaitech3/level1-image-classification-level1-recsys-07

  level1-image-classification-level1-recsys-07 created by GitHub Classroom

  Language:Python52

• zzsza/Boostcamp-AI-Tech-Product-Serving

  부스트캠프 AI Tech - Product Serving 자료

  Language:Python404344

• NVIDIA/apex

  A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

  Language:Python8.3k1.4k

• MaartenGr/KeyBERT

  Minimal keyword extraction with BERT

  Language:Python3.4k343

• myeonghak/DGL-tutorial

  그래프 딥러닝 라이브러리 DGL 쉽게 배우기

  Language:Jupyter Notebook649

• youyoungjang/pytorch-gnn-research

  Various Applications and Descriptions of GNN with Pytorch, Pytorch Geometric.

  Language:Jupyter Notebook316