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applied-ml

📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

attentional_factorization_machine

TensorFlow Implementation of Attentional Factorization Machine

awesome-rspapers

Recommender System Papers

bert4rec

BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

booksource

《第一行代码 第2版》全书源代码

caser_pytorch

A PyTorch implementation of Convolutional Sequence Embedding Recommendation Model (Caser)

clsr

The official implementation of "Disentangling Long and Short-Term Interests for Recommendation" (WWW '22)

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

dccf

[SIGIR'2023] "DCCF: Disentangled Contrastive Collaborative Filtering"

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deep-learning-coursera-1

Deep Learning Specialization by Andrew Ng, deeplearning.ai.

deep_learning-1

Basic Deep Learning

deepctr

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

deepinterestnetwork

deeplearning

Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

deepmatch

A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.

deeprec

An Open-source Toolkit for Deep Learning based Recommendation with Tensorflow.

dgl

Python package built to ease deep learning on graph, on top of existing DL frameworks.

dgsr

[TKDE 2022] The source code of "Dynamic Graph Neural Networks for Sequential Recommendation"

dien

dif-sr

dssrec

Disentangled Self-Supervision in Sequential Recommenders

easyrec

A framework for large scale recommendation algorithms.

fashion-mnist

A MNIST-like fashion product database. Benchmark :point_down:

geolite2-city

This repository provides an alternatively download when GeoLite2-City.mmdb.gz impossible for download from maxind.com

gnnpapers

Must-read papers on graph neural networks (GNN)

graphda

SIGIR 2023 "Graph Collaborative Signals Denoising and Augmentation for Recommendation"

gru4rec

GRU4Rec is the original Theano implementation of the algorithm in "Session-based Recommendations with Recurrent Neural Networks" paper, published at ICLR 2016 and its follow-up "Recurrent Neural Networks with Top-k Gains for Session-based Recommendations". The code is optimized for execution on the GPU.

gru4rec-pytorch

An other implementation of GRU4REC using PyTorch