There are 1 repository under ffm topic.
Easy-to-use,Modular and Extendible package of deep-learning based CTR models .
Factorization Machine models in PyTorch
原理解析及代码实战,推荐算法也可以很简单 🔥 想要系统的学习推荐算法的小伙伴,欢迎 Star 或者 Fork 到自己仓库进行学习🚀 有任何疑问欢迎提 Issues,也可加文末的联系方式向我询问!
Implements of Awesome RecSystem Models with PyTorch/TF2.0
:fire: 全面深入地掌握NDK技术,成为下一波5G时代的浪潮儿~
主流推荐系统Rank算法的实现
基于 Pytorch 实现推荐系统相关的算法
FFM (Field-Awared Factorization Machine) on Spark
some ctr model, implemented by PyTorch, such as Factorization Machines, Field-aware Factorization Machines, DeepFM, xDeepFM, Deep Interest Network
Field-aware factorization machine (FFM) with FTRL
rater, recommender systems. 推荐模型,包括:DeepFM,Wide&Deep,DIN,DeepWalk,Node2Vec等模型实现,开箱即用。
Call Java from C++ and C++ from Java with a variety of old and new projects like JNI, JNA, JNR, FFM, JExtract, GraalVM, JNI-Bind, etc.
A easy library for recommendation system or computational advertising
Unsupervised learning coupled with applied factor analysis to the five-factor model (FFM), a taxonomy for personality traits used to describe the human personality and psyche, via descriptors of common language and not on neuropsychological experiments. Used kmeans clustering and feature scaling (min-max normalization).
Experiment results using FM, FFM and DeepFM algorithms in Criteo Display Advertising Challenge(https://www.kaggle.com/c/criteo-display-ad-challenge) dataset
Apache developers Big-Five personality profiler
Example of direct usage of opengl and glfw (without JNI) with java 18 Foreign Function & Memory API (FFM API)
Parksünder in Frankfurt/Main schnell und einfach melden
Gradle plugin that generates Java bindings from native library headers using Jextract