jeffchen2020,github

advanced-deep-learning-with-keras

Advanced Deep Learning with Keras, published by Packt

ai_tutorial

精华机器学习，NLP，图像识别，深度学习等人工智能领域学习资料，搜索，推荐，广告系统架构及算法技术资料整理

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]

ant-learn-recsys

推荐系统从入门到实战

awesome-deep-learning-papers-for-search-recommendation-advertising

Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.

bandit_simulations

Bandit algorithms simulations for online learning

beijing_house_knowledge

北京买房攻略

book-notes

tf-demo

books

整理一些书籍 ,包含 C&C++ 、git 、Java、Keras 、Linux 、NLP 、Python 、Scala 、TensorFlow 、大数据、推荐系统、数据库、数据挖掘、机器学习、深度学习、算法等。

bookskeeper

对各类图书资源的收集。大量计算机、AI方面书籍。

china_house

**买房相关资料和项目整理，方便查看，持续更新中...

contextual-bandit-news-article-recommendation

Predict and recommend the news articles, user is most likely to click in real time.

deep-ctr

An attempt of training DNN models to predict ad click-through rate, implemented with Theano.

deep-ctr-prediction

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

deep-learning-apps-using-python

Source Code for 'Deep Learning with Applications Using Python' by Navin Kumar Manaswi

deep-learning-quick-reference

Deep Learning Quick Reference, published by Packt

deep_learning_quick_reference

deepctr

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

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.

difacto_dmlc

Distributed FM and LR based on Parameter Server with Ftrl

fm-ffm

FM and FFM implement with tensorflow by Python

handson-ml2

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.