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Building a Recommendation Engine with Scala epub

Building a Recommendation Engine with Scala epub

Building a Recommendation Engine with Scala by Saleem A. Ansari

Building a Recommendation Engine with Scala



Building a Recommendation Engine with Scala download

Building a Recommendation Engine with Scala Saleem A. Ansari ebook
ISBN: 9781785282584
Publisher: Packt Publishing, Limited
Page: 156
Format: pdf


PredictionIO/template-scala-parallel-universal-recommendation Create a new app name, change appName in engine.json; Run pio app new in step #2; Perform pio build , pio train , and pio deploy; To execute some sample queries run . This book is written for those who want to learn the different tools in the Scala ecosystem to build a recommendation engine. Contribute to scala-parallel-universal-recommendation development by creating an Create a new app name, change appName in engine.json; Run pio app new pio build , pio train , and pio deploy; To execute some sample queries run . 25 commits · 2 branches · 6 releases · Fetching contributors v0.2.0. This Recommendation Engine Template has integrated Apache Spark MLlib's Collaborative pio template get PredictionIO/template-scala-parallel- recommendation Now you can build, train, and deploy the engine. This remains the best entry point into Mahout recommender engines of all These are the pieces from which you will build your own recommendation engine . Building a food recommendation engine with Spark / MLlib and Play. PredictionIO Recommendation Engine Template (Scala-based parallelized engine) v0.2.0. Posts about scala written by chimpler. Recommendation engines have become very popular in the last Building a food recommendation engine with Spark / MLlib and Play I'm using Scala 2.10. This section is based on the Recommendation Engine Template. PredictiionIO Template for Multimodal Recommender. PredictionIO E-Commerce Recommendation Engine Template (Scala-based parallelized engine). 4, MongoDB 3.0.2 and Play Framework 2.3.8 with Activator 1.3.2. Create a java project in your favorite IDE and make sure mahout is on the recommendation : recommendations) { System.out.println(recommendation); }. Further, this ID value must be numeric; it is a Java long type through the APIs.





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