book

Practical Machine Learning: Innovations in Recommendation

Name: Practical Machine Learning: Innovations in Recommendation
ISBN: 9781491915387

February 2014

Intermediate to advanced

56 pages

59m

English

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1. Practical Machine Learning
What’s a Person To Do?Making Recommendation Approachable
2. Careful Simplification
Behavior, Co-occurrence, and Text RetrievalDesign of a Simple Recommender
3. What I Do, Not What I Say
Collecting Input Data
4. Co-occurrence and Recommendation
How Apache Mahout Builds a ModelRelevance Score
5. Deploy the Recommender
What Is Apache Solr/Lucene?Why Use Apache Solr/Lucene to Deploy?What’s the Connection Between Solr and Co-occurrence Indicators?How the Recommender WorksTwo-Part Design
6. Example: Music Recommender
Business Goal of the Music MachineData SourcesRecommendations at ScaleA Peek Inside the EngineUsing Search to Make the Recommendations
7. Making It Better
DitheringAnti-floodWhen More Is More: Multimodal and Cross Recommendation
8. Lessons Learned
A. Additional Resources
Slides/VideosBlogBooksTrainingApache Mahout Open Source ProjectLucidWorksElasticsearch
About the Authors

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