Best Practices on Recommendation Systems
-
Updated
Jul 23, 2020 - Python
Best Practices on Recommendation Systems
A collection of small bash scripts for heavy terminal users
Deep learning for recommender systems
Machine Learning Platform and Recommendation Engine built on Kubernetes
Neo4j-based recommendation engine module with real-time and pre-computed recommendations.
RecDB is a recommendation engine built entirely inside PostgreSQL
A C library for product recommendations/suggestions using collaborative filtering (CF)
A Comparative Framework for Multimodal Recommender Systems
Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems
recommenderlab - Lab for Developing and Testing Recommender Algorithms - R package
Towards A Standardized Tag Recommender Benchmarking Framework
Simple recommendation engine implementation built on top of Redis
A simple recommendation engine for Rails/Postgres
Java-Based Context-aware Recommendation Library
电影推荐系统、电影推荐引擎、使用Spark完成的电影推荐引擎
A curated list of repositories for my book Machine Learning Solutions.
Deep learning based image similarity search for product recommendations
Music Recommender System
A simple movie recommendation engine
Basic Movie Recommendation Web Application using user-item collaborative filtering.
Machine learning for beginner(Data Science enthusiast)
[Deprecated] An optimized MapReduce for item‐based collaborative filtering recommendation algorithm with empirical analysis
Recommendation Models in TensorFlow
A lightweight product recommendation system (Item Based Collaborative Filtering) developed in Haskell.
NReco Recommender is a .NET port of Apache Mahout CF java engine (standalone, non-Hadoop version)
Apache Zeppelin notebooks for Recommendation Engines using Keras and Machine Learning on Apache Spark
Pearson correlation coefficient calculator
PHP and wrapping Redis's sorted set APIs for specializing recommending operations.
Add a description, image, and links to the recommendation-engine topic page so that developers can more easily learn about it.
To associate your repository with the recommendation-engine topic, visit your repo's landing page and select "manage topics."