A recommender engine similar to those used by Netflix or Amazon.
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Updated
Mar 26, 2017 - Java
A recommender engine similar to those used by Netflix or Amazon.
A media recommendation web app.
[GIW-MII-UGR-2016-2017] Desarrollo de un Sistema de Recomendación basado en Filtrado Colaborativo "User Based" desde cero y con Mahout Taste
Maidenpool SDK for the Java programming language.
This project is proof-of-concept work of developing Mahout Recommendation Engine. The technology used is Spring Boot framework and MongoDB as the database.
A DIY version of a simple movie recommendation system.
In this project we build docker deployable adaptive recommendation engine for meals to maintain users’ nutritional intake and variety in upcoming meals using Flask. We encode preparation steps of recipes in vector space to find similarities between recipes using math formula. We develop interactive Android App for users to log daily meals.
some examples via spark,hadoop
recommend
A sample of my work from APCS (AP Computer Science) at Homestead High School.
ML Recommendation System Skeleton / Product Comparison Service (Java 11 / MongoDB / Spring)
a Java-based recommendation engine using t-SNE techinal and QuadTree algorithms
Apache Spark Recommendation/Machine Learning Api Service
A recommendation system, complete with UI built using Java in IntelliJ IDEA
Spring Boot Starter for using Mahout as a recommendation engine for item-based collaborative filtering.
Java and Spring demo api for the Oatfin platform
Book Recommendation Service
A Java implementation of Alternating Least Squares (ALS).
An Android App with ML backend to suggest movies based on your continuous rating.
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