Popular GitHub Repositories for Session Aware Recommendation

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

Context aware, pluggable and customizable data protection and de-identification SDK for text and images

A Python implementation of LightFM, a hybrid recommendation algorithm.

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

A unified, comprehensive and efficient recommendation library

A Streamlit-powered Chat Assistant utilizing Ollama's DeepSeek-R1 (1.5B) model for intelligent, context-aware conversations. Designed with an interactive chat interface, adjustable model parameters. It leverages Ollama for local model serving and Streamlit for a responsive UI for text-based interactions.

Sparsity-aware deep learning inference runtime for CPUs

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

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

Jupyter extensions that help you write code faster: Context aware AI Chat, Autocomplete, and Spreadsheet

Pytorch domain library for recommendation systems

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

A framework for large scale recommendation algorithms.

GANimation: Anatomically-aware Facial Animation from a Single Image (ECCV'18 Oral) [PyTorch]

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.