Recommendation Systems with the Elastic Stack

Recommendation Systems with the Elastic Stack

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Summary

Search recommendations are a simple way to direct users to results they might not find on their own. This instructor-led course will walk you through creating and running a simple movie recommendation system using the Elastic Stack and Spark.
Note: This course is a module of the Data Science specialization.

Description

After exploring how the Elastic Stack can be used for recommendations, you will learn how use significant terms aggregations to find "commonly uncommon" recommendations. You will then use Graph, the perfect tool for visualizing the recommendations as you discover them. After completing this course, you will be able to use the Elastic Stack in combination with Spark to make retail-style recommendations.

Topics Covered

  • Creating a Recommendation System with the Elastic Stack
  • Significant Recommendations with Graph
  • Sharing Data Between Elasticsearch and Apache Spark
  • Collaborative Filtering for Recommendations
Download Course Outline

Length

2-3 hours

Duration

1 Day

Audience

Data Scientists, Software Developers

Prerequisites

  • We recommend you have taken Elasticsearch Engineer I and Elasticsearch Engineer II or possess equivalent knowledge. Engineer I and Engineer II teach the concepts that are the foundation upon which all specializations are built.
  • Some familiarity with machine learning is recommended but not required

Setup Requirements

  • Stable internet connection
  • Mac, Linux, or Windows
  • Latest version of Chrome or Firefox (Safari is not 100% supported)
  • Due to virtual classroom JavaScript requirements, we recommend that you disable any ad-blockers and restart your browser before class.

Additional Notes

Virtual Classroom Information
This instructor-led course is only taught in a virtual classroom environment. We encourage participants to set up their systems prior to logging into the training environment the first day of the class. We also encourage being logged into the virtual classroom 15 minutes prior to the start of class each day.

Training Specializations

This course is a module of the Data Science specialization. Find out how our focused Training Specializations can help you with your use case.

General Training Information
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