uplift模型业界应用总结

计算机类专业经典书籍集合，Java、Scala、C/C++、算法、计算机基础、数学、英语等电子书以及互联网大厂技术峰会资料

Extensive tutorials for learning how to build deep learning models for causal inference (HTE) using selection on observables in Tensorflow 2.

A curated list of awesome Machine Learning frameworks, libraries and software.

一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM，xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,DIN, DIEN ... （pytorch, tf2.0）

2021中国翻墙软件VPN推荐以及科学上网避坑，稳定好用。对比SSR机场、蓝灯、V2ray、老王VPN、VPS搭建梯子等科学上网与翻墙软件，中国最新科学上网翻墙梯子VPN下载推荐。

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…

Uplift modeling and causal inference with machine learning algorithms

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…

Datawhale成员整理的面经，内容包括机器学习，CV，NLP，推荐，开发等，欢迎大家star

Implementation of Multi Head Attention Block with example in TF2

Reading list for research topics in multimodal machine learning

Recurrence the recommender paper with Tensorflow2.0

专门为刚开始刷题的同学准备的算法基地，没有最细只有更细，立志用动画将晦涩难懂的算法说的通俗易懂！

LeetCode 刷题攻略：配思维导图，100+经典算法题目刷题顺序、经典算法模板、共40w字的详细图解，以及难点视频题解。按照刷题攻略上的顺序来刷题，让你在算法学习上不再迷茫！🔥🔥给个star支持一下吧！🚀

《Pytorch模型训练实用教程》中配套代码

PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet

PyTorch Tutorial for Deep Learning Researchers

Awesome Neural Logic and Causality: MLN, NLRL, NLM, etc. 因果推断，神经逻辑，强人工智能逻辑推理前沿领域。

广告点击率(CTR)预测经典模型 GBDT + LR 理解与实践（附数据 + 代码）

1st place solution for the AntaiCup-International-E-commerce-Artificial-Intelligence-Challenge

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

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

kaggle competition iMet Collection 2019 Classify the multi-­‐label images classification according to their given label using a ResNet50 . build the model from the scratch

Implementation of AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks

This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches"

An industrial deep learning framework for high-dimension sparse data

Classic papers and resources on recommendation