Solution Accelerator

Recommendation Engines for Personalization

Pre-built code, sample data and step-by-step instructions ready to go in a Databricks notebook

Increase conversion with personalized recommendations

Customers have different needs at each stage of the buyer journey. Choose the right recommender model for your scenario. Have a cold start problem? Try content-based recommenders. Nudging an existing customer to add to their cart? Wide-and-deep recommenders can help.

NOTEBOOK 1

Imaged-based recommendations

Build a similarity-based image recommendation system for e-commerce that takes into account the visual similarity of items as an input for making product recommendations.

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NOTEBOOK 2

Market-based recommendations

Build a recommender that leverages product affinities to suggest additional items.

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NOTEBOOK 3

Wide-and-deep recommendations

Build a wide-and-deep recommender with collaborative filters that takes advantage of patterns of repeat purchases to suggest both previously purchased and related products.

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Resources

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