Popular GitHub Repositories for Phone Recommendation

MiniCPM-V 4.5: A GPT-4o Level MLLM for Single Image, Multi Image and Video Understanding on Your Phone

MiniCPM-o 2.6: A GPT-4o Level MLLM for Vision, Speech and Multimodal Live Streaming on Your Phone

OpenVINO? is an open source toolkit for optimizing and deploying AI inference

深度学习面试宝典（含数学、机器学习、深度学习、计算机视觉、自然语言处理和SLAM等方向）

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

A Python scikit for building and analyzing recommender systems

AI + Data, online. https://vespa.ai

Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG

A Python implementation of LightFM, a hybrid recommendation algorithm.

A unified, comprehensive and efficient recommendation library

Recommendation Algorithm大规模推荐算法库，包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、AITM，DSIN，SIGN，IPREC、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESMM、ESCMM, MAML、xDeepFM、DeepFEFM、NFM、AFM、RALM、DMR、GateNet、NAML、DIFM、Deep Crossing、PNN、BST、AutoInt、FGCNN、FLEN、Fibinet、ListWise、DeepRec、ENSFM，TiSAS，AutoFIS等，包含经典推荐系统数据集criteo 、movielens等

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

Pytorch domain library for recommendation systems

? Monitor deep learning model training and hardware usage from your mobile phone ?

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.

An android AI agent can automatically operate your mobile phone

A framework for large scale recommendation algorithms.

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

Deep learning for recommender systems

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)