What is the role of explainable AI (XAI) in building trust and transparency in recommendation systems?

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 ... This system uses different sensors for extracting data continuously regarding temperature, PH and Turbidity etc. These parameters can be analysed in real-time ... Feb 13, 2023 ... The proposed collaborative filtering (CF) method categorizes active learners into one learner group. The proposed model has experimented on ... May 1, 2019 ... Microsoft has provided a GitHub repository with Python best practice examples to facilitate the building and evaluation of recommendation systems using Azure ... Jun 19, 2024 ... Recommendation systems rely on big data analytics and machine learning (ML) algorithms to find patterns in user behavior data and recommend ... Aug 9, 2023 ... Using more advanced machine learning models, like Two Towers neural networks, we've been able to make the Explore recommendation system even ... Moreover, recommender systems are among the most powerful machine learning systems that online retailers implement in order to drive incremental revenue. Aug 22, 2017 ... Netflix uses machine learning and algorithms to help break viewers' preconceived notions and find shows that they might not have initially chosen. Recommended Citation. Bommireddy, Durga Rajesh, "Recommendation System using machine learning for fertilizer prediction" (2024). Electronic Theses, Projects, ... Nov 2, 2016 ... My answer would be that while a recommendation system can use supervised or unsupervised learning, it is neither of them, because it's a concept at a different ...