mulkong

mulkong's Stars

• guyulongcs/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising

  Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Ranking (CTR/CVR prediction), Post Ranking, Large Model (Generative Recommendation, LLM), Transfer learning, Reinforcement Learning and so on.

  Language:Python1.5k230

• instantX-research/InstantStyle

  InstantStyle: Free Lunch towards Style-Preserving in Text-to-Image Generation 🔥

  Language:Jupyter Notebook1.7k108

• instantX-research/InstantID

  InstantID: Zero-shot Identity-Preserving Generation in Seconds 🔥

  Language:Python11.3k823

• alebcay/openlens-node-pod-menu

  Node and pod menus for OpenLens

  Language:TypeScript84149

• google-ai-edge/mediapipe

  Cross-platform, customizable ML solutions for live and streaming media.

  Language:C++28.1k5.2k

• gauravchak/two_tower_models

  We write sample code for two tower models for retrieval and add RLHF/RLAIF style alignment with a ranking model to make the retrieval more aligned with the ranking model on top

  Language:Python386

• benfred/implicit

  Fast Python Collaborative Filtering for Implicit Feedback Datasets

  Language:Python3.6k610

• Project-HAMi/HAMi

  Heterogeneous AI Computing Virtualization Middleware

  Language:Go1.1k234

• maciejkula/spotlight

  Deep recommender models using PyTorch.

  Language:Python3k425

• yunseongcho/chatgpt_paper_review

  chatgpt를 통한 paper review 코드입니다.

  Language:Python4

• bentoml/BentoML

  The easiest way to serve AI apps and models - Build Model Inference APIs, Job queues, LLM apps, Multi-model pipelines, and more!

  Language:Python7.2k797

• mulkong/Kubernetes_Study

  2

• YushenLi807/WWW24-RAT

  The code for the paper "RAT: Retrieval-Augmented Transformer for Click-Through Rate Prediction" (WWW 24 short paper)

  Language:Python282

• SeongBeomLEE/RecsysTutorial

  추천시스템 논문을 읽고 구현한 Code가 저장된 Repository

  Language:Jupyter Notebook6711

• RUCAIBox/RecBole

  A unified, comprehensive and efficient recommendation library

  Language:Python3.5k622

• NVIDIA/DeepLearningExamples

  State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

  Language:Jupyter Notebook13.7k3.3k

• run-llama/gmail-extractor

  Language:Python11819

• shenweichen/DeepCTR-Torch

  【PyTorch】Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

  Language:Python3.1k710

• reczoo/FuxiCTR

  A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io

  Language:Python976164

• pytorch/torchrec

  Pytorch domain library for recommendation systems

  Language:Python2k455

• gilbutITbook/kiamol

  Language:C#3430

• NVIDIA/DeepRecommender

  Deep learning for recommender systems

  Language:Python1.7k338

• recommenders-team/recommenders

  Best Practices on Recommendation Systems

  Language:Python19.5k3.1k

• feast-dev/feast

  The Open Source Feature Store for Machine Learning

  Language:Python5.7k1k

• kakao/recoteam

  카카오 추천팀 공개 리포지토리입니다.

  Language:Jupyter Notebook33418

• lim-hyo-jeong/Prompt-Enhancer

  Prompt Engineering at Your Fingertips!

  Language:Python4513

• hpcaitech/Open-Sora

  Open-Sora: Democratizing Efficient Video Production for All

  Language:Python22.9k2.3k

• deep-diver/Vid2Persona

  This project breathes life into video characters by using AI to describe their personality and then chat with you as them.

  Language:Jupyter Notebook456

• UpstageAI/dataverse

  The Universe of Data. All about data, data science, and data engineering

  Language:Python52352

• doku-study/doku-study

  【한글자막】 Docker & Kubernetes : 실전 가이드 강의를 듣고 함께 공부한 것을 공유합니다.

  8