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ad-papers

Papers on Computational Advertising

ai-recommendersystem

该仓库尝试整理推荐系统领域的一些经典算法模型

algorithm-practice-in-industry

搜索、推荐、广告、用增等工业界实践文章收集（来源：知乎、Datafuntalk、技术公众号）

alibaba-custermers-interaction-dataset

all-about-the-gan

All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN

attention

some attention implements

attention-mechanisms

Implementations for a family of attention mechanisms, suitable for all kinds of natural language processing tasks and compatible with TensorFlow 2.0 and Keras.

awesome-python-cn

Python资源大全中文版，包括：Web框架、网络爬虫、模板引擎、数据库、数据可视化、图片处理等，由伯乐在线持续更新。

awesome-tensorflow

TensorFlow - A curated list of dedicated resources http://tensorflow.org

bert

TensorFlow code and pre-trained models for BERT

bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

bert-chinese-text-classification-and-deployment

简单高效的Bert中文文本分类模型开发和部署

bert4keras

keras implement of transformers for humans

bert4rec

BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer

chinese-bert-wwm

Pre-Training with Whole Word Masking for Chinese BERT（中文BERT-wwm系列模型）

competition

参加过的比赛记录，包括代码和经验和其他文件

convert_to_tfrecord

Tutorial:Convert your data to tfrecord

coolplayspark

酷玩 Spark: Spark 源代码解析、Spark 类库等

ctr_prediction

CTR prediction using FM FFM and DeepFM

ctrmodel

CTR prediction model based on spark(LR, GBDT, DNN)

cube-studio

云原生一站式机器学习平台，多租户，notebook在线开发，拖拉拽任务流编排，多机多卡分布式训练，超参搜索，推理服务，多集群调度，多项目组资源组，边缘计算，大模型实时训练

datapreprocessing

data preprocessing for tensorflow model

decrs

Deconfounded Recommendation for Alleviating Bias Amplification

deep-ctr-prediction

CTR prediction models based on deep learning(基于深度学习的广告CTR预估模型)

deep-learning-papers-reading-roadmap

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

deepctr

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

deepinterestnetwork

deeplearning

深度学习相关的模型训练、评估和预测相关代码

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

deeplearning-models

A collection of various deep learning architectures, models, and tips