Building a Recommendation Engine with Scala

Saleem Ansari



Learn to use Scala to build a recommendation engine from scratch and empower your website users

With an increase of data in online e-commerce systems, the challenges in assisting users with narrowing down their search have grown dramatically. The various tools available in the Scala ecosystem enable developers to build a processing pipeline to meet those challenges and create a recommendation system to accelerate business growth and leverage brand advocacy for your clients.

This book provides you with the Scala knowledge you need to build a recommendation engine.

You'll be introduced to Scala and other related tools to set the stage for the project and familiarise yourself with the different stages in the data processing pipeline, including at which stages you can leverage the power of Scala and related tools. You'll also discover different machine learning algorithms using MLLib.

As the book progresses, you will gain detailed knowledge of what constitutes a collaborative filtering based recommendation and explore different methods to improve users’ recommendation.

Table of Contents

1: INTRODUCTION TO SCALA AND MACHINE LEARNING
2: DATA PROCESSING PIPELINE USING SCALA
3: CONCEPTUALIZING AN E-COMMERCE STORE
4: MACHINE LEARNING ALGORITHMS
5: RECOMMENDATION ENGINES AND WHERE THEY FIT IN?
6: COLLABORATIVE FILTERING VERSUS CONTENT-BASED RECOMMENDATION ENGINES
7: ENHANCING THE USER EXPERIENCE
8: LEARNING FROM USER FEEDBACK



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