The Recommend product from Algolia uses machine-learning to suggest products or content that will interest customers, with a focus on trends and popular items across the entire catalog or within specific facets. The new Trends models are collaborative-filtering models that look for product trends without being restricted to recommendations based on a single product, and can be used to recommend popular categories or attributes on the homepage. To use the Recommend models, users need to have their products stored in an Algolia index, track trends for items or facet values across the index, and train one of two new models using conversion events captured from users, such as purchases or favorites. Once trained, the model can provide up to 30 recommendations globally or within a specified facet. The Recommend front-end UI libraries make it easy to add Trending items and Trending facet values to an application, allowing customers to discover new items during their entire journey on the site.