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12306

12306智能刷票，订票

ai_lab_5

黑白棋、博弈树、剪枝

aitm

TensorFlow implementation of Adaptive Information Transfer Multi-task (AITM) framework. Code for the paper accepted by KDD21: Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising. [https://arxiv.org/abs/2105.08489]

algonotes

公众号【浅梦学习笔记】文章汇总:包含 排序&CXR预估，召回匹配，用户画像&特征工程，推荐搜索综合 计算广告，大数据，图算法，NLP&CV，求职面试 等内容

automatedparaphrase

Automated paraphrases Generation

autoticket

大麦网自动抢票工具

awesome-multi-task-learning

A list of multi-task learning papers and projects.

awesome-resume-for-chinese

:page_facing_up: 适合中文的简历模板收集（LaTeX，HTML/JS and so on）由 @hoochanlon 维护

chinese-word-vectors

100+ Chinese Word Vectors 上百种预训练中文词向量

concert_ticket

大麦网演唱会抢票程序

cstwa

ctr

CTR模型代码和学习笔记总结

datasets-for-recommender-systems

This is a repository of a topic-centric public data sources in high quality for Recommender Systems (RS)

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）

deep_recommenders

Deep Recommenders

deepctr

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

dsanforaaai2021

easyrec

A framework for large scale recommendation algorithms.

easyreversi

h-transformer-1d

Implementation of H-Transformer-1D, Hierarchical Attention for Sequence Learning

har-ranking-model

Utilizing hierarchical attention to rank query-doc pairs

hgnn-ac

Source code of "WWW21 - Heterogeneous Graph Neural Network via Attribute Completion"

hin-datasets-for-recommendation-and-network-embedding

Heterogeneous Information Network Datasets for Recommendation and Network Embedding

kepn

lambdaranknn

LambdaRank Neural Network model using Keras.

lattice

[ACMMM 2021] PyTorch implementation for "Mining Latent Structures for Multimedia Recommendation"

local-attention

An implementation of local windowed attention for language modeling

longformer

Longformer: The Long-Document Transformer

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。

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