Recommenders

Basic recommenders that are easy to understand and implement, as well as fast to trainCreated by me on dreamstudio.ai.Recommender systems are algorithms designed to provide user recommendations based on their past behavior, preferences, and interactions. Becoming integral to various industries, including e-commerce, entertainment, and advertising, recommender systems improve user experience, increase customer retention, and drive sales.While various advanced recommender systems exist, today I want to show you one of the…

Photo by Nathan Engel: https://www.pexels.com/photo/time-lapse-photography-of-car-lights-in-front-of-cinema-436413/Hello readers,For those of you who haven’t read the previous part, here is the link:In that article, I present the MovieLens-1M dataset (a movie recommendations dataset that contains 1 million ratings for movies made by different users) along with some exploratory data analysis and try out some classical recommender systems algorithms. Although, that article is not a pre-requisite and you will be able to…

Integrating Privacy with Reinforcement LearningPic Credit: Exploring the Unknown by Soma Biswas (Flickr: link, Reposted with Permission)In this article, we focus on enabling recommendations in a conversational context. More concretely, we consider an app that is able to converse with the user, providing interesting and relevant information to the user; either (on-demand) in response to a specific user query or proactively in the form of timely and relevant alerts.Interaction Personalization: While chatbots today are able…