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ad-papers

Papers on Computational Advertising

adversarialnetspapers

The classical paper list with code about generative adversarial nets

algorithm

alphafm

Multi-thread implementation of Factorization Machines with FTRL for binary-class classification problem.

alphaplm

Multi-thread implementation of Piece-wise Linear Model(PLM) or Mixture of LR(MLR) with FTRL for binary-class classification problem.

angel

A Flexible and Powerful Parameter Server for large-scale machine learning

awesome-deep-learning-papers

The most cited deep learning papers

awesome-machine-learning-cn

机器学习资源大全中文版，包括机器学习领域的框架、库以及软件

awesome-tensorflow-chinese

Awesome-TensorFlow-Chinese，TensorFlow 中文资源精选，官方网站，安装教程，入门教程，实战项目，学习路径。QQ群：522785813

chatbotcourse

自己动手做聊天机器人教程

cpp_concurrency_in_action

:book: 作为对《C++ Concurrency in Action》英文版的中文翻译。

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 .

deeplearningbook-chinese

Deep Learning Book Chinese Translation

didi

difacto_dmlc

Distributed FM and LR based on PS with Ftrl

dmtk

Microsoft Distributed Machine Learning Toolkit

esl-cn

The Elements of Statistical Learning (ESL)的中文翻译、代码实现及其习题解答。

field-aware-factorization-machine-mpi

LR、FM、FFM model solved by ftrl and sgd parallel on MPI

field-aware-factorization-machine-ps

LR model solved by ftrl and sgd parallel on parameter server(ps-lite). FM、FFM model in the future

fm_dmlc

Distributed FM and LR based on Rabit with Lbfgs

foundations_for_deep_learning

Building a scalable foundation for deep learning

fun-rec

推荐系统入门教程，在线阅读地址：https://datawhalechina.github.io/fun-rec/

kaggle-2014-criteo

lambdafm

Multi-thread implementation of lambdaFM with FTRL for ranking problem. LambdaFM is a learning-to-rank algorithm by combining LambdaRank and Factorization Machines.

libble-spark

libffm-ftrl

libffm with ftrl updater

libfm_with_bpr

lightgbm

A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.

machinelearning

Basic Machine Learning and Deep Learning