recommendation-algorithm

Best Practices on Recommendation Systems

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

A collection of resources for Recommender Systems (RecSys)

OpenRec is an open-source and modular library for neural network-inspired recommendation algorithms

⚡ A python fast implementation of the famous SVD algorithm popularized by Simon Funk during Netflix Prize

pyRecLab is a library for quickly testing and prototyping of traditional recommender system methods, such as User KNN, Item KNN and FunkSVD Collaborative Filtering. It is developed and maintained by Gabriel Sepúlveda and Vicente Domínguez, advised by Prof. Denis Parra, all of them in Computer Science Department at PUC Chile, IA Lab and SocVis Lab.

Machine Learning (EE 5184) in NTU

This is a new deep learning model for recommender system, which we called PHD

PHP and wrapping Redis's sorted set APIs for specializing recommending operations.

一个基于SSM框架与物品的协同过滤算法(ItemCF)的简单电子书推荐系统

An expert system I wrote in high school to recommend fiction to the casual reader. Unfortunately the rule engine it sends commands to is dated and not open source.

商品关联关系挖掘，使用Spring Boot开发框架和Spark MLlib机器学习框架，通过FP-Growth算法，分析用户的购物车商品数据，挖掘商品之间的关联关系。项目对外提供RESTFul接口。

Finding recommendations between them all. Work in progress.

Code for RecSys'19 paper: Leveraging Post-click Feedback for Content Recommendations

Collaborative filtering recommendation system. Recommendation algorithm using collaborative filtering. Topics: Ranking algorithm, euclidean distance algorithm, slope one algorithm, filtragem colaborativa.

A real-time news scraping and recommendation system

Recommendation engine in Java. Based on an ALS algorithm (Apache Spark). Train a new model after N seconds.

[PY]thon [R]ec[O]mmender [S]ystems library

Implementations of the EigenRec algorithm

A book recommendations application that works on the Dash framework and implements content based filtering using TF-IDF and cosine similarity.

A lightweight recommendation algorithm framework based on LycorisNet.

Movie recommender AI.

🔱 Some recognized algorithms[Decision Tree, Adaboost, Perceptron, Clustering, Neural network etc. ] of machine learning and pattern recognition are implemented from scratch using python. Data sets are also included to test the algorithms.

MIT xPRO Data Science Course Movie Recommendations Case Study

Board game recommendation engine

Code the Curve 2020

Behavior based video recommendation, global keyboard control and ads block for Youtube

In this Movie Dataset I have used my Basic Knowledge of Recommendation Systems. I have used the Concept of Content -Based Recommendation System to Recommend that If a User Watched a Particular Movie than Which Other Movies He/She is going to like or watch.

Recommends movies based on user input and a a pre-trained NMF-model with a browser-based user interface (Flask). Optionally outputs movie trailers for recommendations from YouTube.