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

CTR Algorithm

根据论文, 博客, 知乎等方式学习一些CTR相关的算法
理解原理并自己动手来实现一遍
pytorch & tf2.0
保持一颗学徒的心！

Model	pytorch	tensorflow2.0	paper
LR	✔️	✔️	\
FM	✔️	✔️	Factorization Machines, 2010.
FFM	✔️	✔️	Field-aware Factorization Machines for CTR Prediction, 2015.
AFM	✔️	✔️	Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks, 2017.
DeepFM	✔️	✔️	DeepFM: A Factorization-Machine based Neural Network for CTR Prediction, 2017.
PNN	✔️	✔️	Product-based Neural Networks for User Response Prediction, 2016.
XDeepFM	✔️	✔️	xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems, 2018.
DCN	✔️	✔️	Deep & Cross Network for Ad Click Predictions, 2017.
AutoInt	✔️	✔️	AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks, 2018.
DIN	✔️	✔️	Deep Interest Network for Click-Through Rate Prediction,2018
DIEN	✔️	✔️	Deep Interest Evolution Network for Click-Through Rate Prediction,2019
FiBiNET	✔️	✔️	FiBiNET: Combining Feature Importance and Bilinear feature Interaction for Click-Through Rate Prediction,2019
DCN-V2	✔️	✔️	Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems,2020
DIFM	✔️	✔️	A Dual Input-aware Factorization Machine for CTR Prediction,2020
AFN	✔️	✔️	Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions,2020
ONN	✔️	✔️	Operation-aware Neural Networks for User Response Prediction,2019