What are some promising directions for future research in recommendation systems?

Build a recommendation system using collaborative filtering and machine learning. This document outlines the reference architecture for two functional machine Learning (ML) retail use cases. It was developed on VMware Cloud Foundation 4.0 ... This system uses different sensors for extracting data continuously regarding temperature, PH and Turbidity etc. These parameters can be analysed in real-time ... Feb 27, 2023 ... Recommender Systems Algorithms and Techniques · Matrix Factorization · Deep Neural Networks · Contextual Sequence Learning · Wide and Deep. Jan 19, 2023 ... How Netflix Utilizes Machine Learning in its Recommendation System ... Netflix uses machine learning techniques, including matrix factorization, ... Jan 15, 2021 ... However, a new trend has emerged in the field since the introduction of deep reinforcement learning (DRL), which made it possible to apply RL to ... The main objective of the Movie Recommendation System is to develop an algorithm that predicts movies a user is most likely to enjoy. By using machine learning ... 3 days ago ... Gained familiarity with various machine learning algorithms used in recommendation systems, such as matrix factorization and deep learning ... This repository contains Deep Learning based articles, papers and repositories for Recommendation Systems. kNN is a machine learning algorithm to find clusters of similar users based on common book ratings, and make predictions using the average rating of top-k ...