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Search results for spark collaborative filtering
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11 search results found
Recommendationsystem
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190
Book recommender system using collaborative filtering based on Spark
Spotify Song Recommendation Ml
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52
UC Berkeley team's submission for RecSys Challenge 2018
Movie Recommender Demo
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50
This project walks through how you can create recommendations using Apache Spark machine learning. There are a number of jupyter notebooks that you can run on IBM Data Science Experience, and there a live demo of a movie recommendation web application you can interact with. The demo also uses IBM Message Hub (kafka) to push application events to topic where they are consumed by a spark streaming job running on IBM BigInsights (hadoop).
Spark Cassandra Collabfiltering
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22
Collaborative filtering with MLLib on Spark based on data in Cassandra
Recommender Systems For Implicit Feedback Datasets
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14
Matrix Factorization augmented with customer item meta data
Recommendbyitemcf
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11
Hadoop mapreduce. 基于ItemCF的协同过滤 物品推荐系统 Collaborative filtering goods recommendation system based on ItemCF
Als Ncg
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9
NCG acceleration of ALS computing low rank matrix factorizations for Collaborative Filtering
Amazon Product Recommendation Cf Als Spark
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9
We have chosen Amazon product sales data set comprising of sales activity and user ratings for each product. The idea is to create a product suggestion/recommendation system for each user based on his previous purchases and his rating for each one. A Collaborative Filtering model is built to predict the virtual ratings for the product that the user did not purchase. The system predicts the user rating for all the items and we display the products which user may be like, buy and rate higher.
Kafka Spark Product Recommendation
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Python script demonstrating spark streaming and Kafka implementation using an e-commerce website like product recommendation engine based on item-based collaborative filtering. 🐍. 💥
Movie_recommender_system_scala
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Build a movie recommender system using Collaborative Filtering by leveraging Spark in Scala
Recommendation System
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5
A movie recommendation system trained on the MovieLens 20 Million dataset. This system makes use of Collaborative filtering methods to come up with recommendations for a particular user.
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