shenweichen/DeepCTR

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

Language: Python - Size: 7.33 MB - Last synced: about 18 hours ago - Pushed: 4 months ago - Stars: 7,392 - Forks: 2,186

aslupin/Encoder-Utility

A program that can custom tools by user for encoding video and audio ,fansuber can define video/audio existing.

Language: HTML - Size: 105 MB - Last synced: 4 days ago - Pushed: over 5 years ago - Stars: 0 - Forks: 0

shibing624/rater

rater, recommender systems. 推荐模型，包括：DeepFM，Wide&Deep，DIN，DeepWalk，Node2Vec等模型实现，开箱即用。

Language: Python - Size: 42.1 MB - Last synced: 3 days ago - Pushed: over 3 years ago - Stars: 38 - Forks: 5

collab-uniba/personality

Apache developers Big-Five personality profiler

Language: Python - Size: 3.52 MB - Last synced: 10 days ago - Pushed: 10 days ago - Stars: 9 - Forks: 3

aksnzhy/xlearn

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

Language: C++ - Size: 10.7 MB - Last synced: 16 days ago - Pushed: 9 months ago - Stars: 3,079 - Forks: 519

ZiyaoGeng/RecLearn

Recommender Learning with Tensorflow2.x

Language: Python - Size: 109 MB - Last synced: 19 days ago - Pushed: about 2 years ago - Stars: 1,810 - Forks: 494

JsonChao/Awesome-Android-NDK

:fire: 全面深入地掌握NDK技术，成为下一波5G时代的浪潮儿~

Size: 146 KB - Last synced: 9 days ago - Pushed: almost 2 years ago - Stars: 199 - Forks: 27

rixwew/pytorch-fm

Factorization Machine models in PyTorch

Language: Python - Size: 5.57 MB - Last synced: 20 days ago - Pushed: about 2 months ago - Stars: 985 - Forks: 219

JianzhouZhan/Awesome-RecSystem-Models

Implements of Awesome RecSystem Models with PyTorch/TF2.0

Language: Python - Size: 916 KB - Last synced: 4 days ago - Pushed: about 4 years ago - Stars: 253 - Forks: 68

duoan/xlearn Fork of aksnzhy/xlearn

High Performance, Easy-to-use, and Scalable Machine Learning Package (C++, Python, R)

Language: C++ - Size: 6.38 MB - Last synced: about 1 month ago - Pushed: about 6 years ago - Stars: 0 - Forks: 0

duoan/kaggle_criteo_ctr_challenge

kaggle criteo ctr challenge

Language: Jupyter Notebook - Size: 1.16 MB - Last synced: about 1 month ago - Pushed: over 5 years ago - Stars: 3 - Forks: 2

etveritas/xlearn Fork of aksnzhy/xlearn

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

Language: C++ - Size: 10.4 MB - Last synced: about 2 months ago - Pushed: almost 5 years ago - Stars: 2 - Forks: 0

aploese/jnhw

JNI Header Wrapper a lightwight alternative to JNA or JNR (V 4.0.0-SNAPSHOT in branch FFM uses JEP 454: Foreign Function & Memory API)

Language: Java - Size: 17.1 MB - Last synced: about 2 months ago - Pushed: about 2 months ago - Stars: 2 - Forks: 0

DSXiangLi/CTR

CTR模型代码和学习笔记总结

Language: Python - Size: 29.9 MB - Last synced: about 2 months ago - Pushed: almost 3 years ago - Stars: 364 - Forks: 92

Hourout/CTR-keras

Tensorflow2.x implementations of CTR（LR、FM、FFM)

Language: Python - Size: 57.6 KB - Last synced: about 2 months ago - Pushed: almost 3 years ago - Stars: 73 - Forks: 18

coralblocks/JavaToCppAndBack

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.

Language: C++ - Size: 4.05 MB - Last synced: 5 months ago - Pushed: 5 months ago - Stars: 11 - Forks: 3

QikaiXu/Recommender-System-Pytorch

基于 Pytorch 实现推荐系统相关的算法

Language: Jupyter Notebook - Size: 15.2 MB - Last synced: 6 months ago - Pushed: over 2 years ago - Stars: 128 - Forks: 26

jc-LeeHub/Recommend-System-tf2.0

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！

Language: Python - Size: 2.47 MB - Last synced: 7 months ago - Pushed: over 2 years ago - Stars: 569 - Forks: 198

tangxyw/RecAlgorithm

主流推荐系统Rank算法的实现

Language: Python - Size: 362 KB - Last synced: 7 months ago - Pushed: 7 months ago - Stars: 104 - Forks: 28

aldente0630/ctr_prediction

Experiment results using FM, FFM and DeepFM algorithms in Criteo Display Advertising Challenge(https://www.kaggle.com/c/criteo-display-ad-challenge) dataset

Language: Jupyter Notebook - Size: 1010 KB - Last synced: 8 months ago - Pushed: about 4 years ago - Stars: 9 - Forks: 3

massquantity/Ftrl-FFM

Field-aware factorization machine (FFM) with FTRL

Language: C++ - Size: 3.75 MB - Last synced: 4 months ago - Pushed: 9 months ago - Stars: 35 - Forks: 16

olvb/pyheal

Pure Python implementation of Telea FMM inpainting

Language: Python - Size: 6.31 MB - Last synced: 9 months ago - Pushed: over 3 years ago - Stars: 34 - Forks: 6

Lovsan/Ruutu-Downloader

Ruutu + Downloader

Language: Visual Basic - Size: 39.1 KB - Last synced: 10 months ago - Pushed: about 6 years ago - Stars: 1 - Forks: 0

VinceShieh/spark-ffm

FFM (Field-Awared Factorization Machine) on Spark

Language: Scala - Size: 305 KB - Last synced: 7 months ago - Pushed: almost 6 years ago - Stars: 104 - Forks: 44

YasPHP/The-Five-Factor-Personality-Test

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).

Language: Jupyter Notebook - Size: 232 KB - Last synced: about 1 year ago - Pushed: almost 3 years ago - Stars: 10 - Forks: 4

Ageneh/wd-todo

Size: 6.84 KB - Last synced: about 1 year ago - Pushed: over 4 years ago - Stars: 0 - Forks: 0

fispact/FFM

Fispact File Maker

Language: JavaScript - Size: 252 KB - Last synced: over 1 year ago - Pushed: over 4 years ago - Stars: 0 - Forks: 0

andreasbrett/FalschparkmelderFFM

Parksünder in Frankfurt/Main schnell und einfach melden

Language: PowerShell - Size: 225 KB - Last synced: over 1 year ago - Pushed: almost 6 years ago - Stars: 0 - Forks: 0