aiyaaa Goto Github PK

adtfk

Codes for WWW 2022 paper [Attentively Dual Transfer Motivation-Aware Interaction Representation for Cross-Domain Recommendation]

ai-job-notes

AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）

al-interview

算法岗知识点、面经

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/自然语言处理(NLP)/深度学习(Deep Learning)/机器学习(Machine Learning)/C/C++/Python/面试笔记，此外，还包括创建者看到的所有机器学习/深度学习面经中的问题。 除了其中 DL/ML 相关的，其他与算法岗相关的计算机知识也会记录。 但是不会包括如前端/测试/JAVA/Android等岗位中有关的问题。

anr

Code for our CIKM 2018 paper titled "ANR: Aspect-based Neural Recommender"

asdae

bi-tgcf

Cross Domain Recommendation via Bi-directional Transfer Graph Collaborative Filtering Networks

catn

The implementation of SIGIR 2020 paper "CATN: Cross-Domain Recommendation for Cold-Start Users via Aspect Transfer Network“, Cheng Zhao, Chenliang Li, Rong Xiao, Hongbo Deng and Aixin Sun

conet

pytorch templete

copycode

darec

Pytorch implementation of DARec: Deep Domain Adaptation for Cross-Domain Recommendation via Transferring Rating Patterns

deep-learning-interview-book

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）

deepfm

a deepFM model using MXNET

dlrm

An implementation of a deep learning recommendation model (DLRM)

emcdr

An Embedding and Mapping framework for Cross-Domain Recommendation.

esrm-kg

filedownloaddemo

实现功能有多线程下载、断点下载、多任务并行下载、显示下载进度及下载速度等功能，亲测下载速度能与UC浏览器相媲美。

fullstack-tutorial

🚀 fullstack tutorial 2021，后台技术栈/架构师之路/全栈开发社区，春招/秋招/校招/面试

ga-dtcdr

This is the model in "A Graphical and Attentional Framework for Dual-Target Cross-Domain Recommendation" (IJCAI2020). GA-DTCDR is an optimized model for DTCDR ("DTCDR: A Framework for Dual-Target Cross-Domain Recommendation" in CIKM2019).

interview-notes

包含机器学习、深度学习、图像处理、c++等视觉算法岗面试必备基础知识

interview_internal_reference

2021年最新总结，阿里，腾讯，百度，美团，头条等技术面试题目，以及答案，专家出题人分析汇总。

kdd2018_mpcn

Code for our KDD 2018 Paper "Multi-Pointer Co-Attention Networks for Recommendation"

leetcode

LeetCode刷题记录与面试整理

mac-network

Implementation for the paper "Compositional Attention Networks for Machine Reasoning" (Hudson and Manning, ICLR 2018)

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

mvin

MVIN: Learning Multiview Items for Recommendation, SIGIR 2020

narre

This is our implementation of NARRE:Neural Attentional Regression with Review-level Explanations

nlp_ability

总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

ppgn

The implementation of "Cross-Domain Recommendation via Preference Propagation GraphNet“, Cheng Zhao, Chenliang Li, Cong Fu, https://doi.org/10.1145/3357384.3358166

pystack

Scripts for processing stack exchange data dump