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Concept

Recommender system

Related lectures (27)

Recommender Systems: Basics and Techniques

Covers collaborative filtering and content-based methods for recommender systems, addressing cold start problems and making predictions.

Recommender Systems

Explores the evolution and impact of recommender systems, covering information retrieval, collaborative filtering, and different recommendation algorithms.

Recommender Systems: Personalized Recommendations for Users

Delves into challenges of content personalization, focusing on web recommendations and personalized newsletters.

Recommender Systems and Structure Discovery

Explores recommender systems, latent factor models, and clustering algorithms for structure discovery.

Gaussian Mixture Models: Applications in Recommender Systems MOOC: Introduction to optimization on smooth manifolds: first order methods

Explores the applications of Gaussian Mixture Models in recommender systems and real-world scenarios like the Roomba robot.

Neuroscience Dataset Recommendation MOOC: Simulation Neurocience

Covers a tutorial on recommending similar neuroscience datasets using knowledge embeddings.

KNN: Nearest Neighbor Classifier

Covers the k-Nearest-Neighbor classifier, hand-written digit recognition, multi-class k-NN, data reduction, applications, graph construction, limitations, and the curse of dimensionality.

Introduction to Machine Learning

Covers the basics of Machine Learning, including recognizing hand-written digits, supervised classification, decision boundaries, and polynomial curve fitting.

Machine Learning Basics

Introduces the basics of machine learning, covering supervised classification, decision boundaries, and polynomial curve fitting.

Machine Learning for Behavioral Data

Introduces a course on Machine Learning for Behavioral Data at EPFL, covering ML algorithms, data handling, and model evaluation.

Recommender Systems: Matrix Factorization

Explores matrix factorization in recommender systems, covering optimization, evaluation metrics, and challenges in scaling.

Recommender Systems Log in to Mediaspace to watch this video

Explores recommender systems, collaborative filtering, content-based recommendations, similarity metrics, and advanced methods like matrix factorization.

Recommender Systems: Text Classification & Naïve Bayes Log in to Mediaspace to watch this video

Explores text classification using Naïve Bayes in content-based recommenders.

Matrix Factorization: Optimization and Evaluation Log in to Mediaspace to watch this video

Explores matrix factorization optimization, evaluation methods, and challenges in recommendation systems.

Recommender Systems: MovieLens Dataset Log in to Mediaspace to watch this video

Covers implementing recommender systems using the MovieLens dataset and evaluating them with RMSE and MAE metrics.

Recommender Systems: Part 1 Log in to Mediaspace to watch this video

Introduces recommender systems, collaborative filtering, content-based recommendation, similarity metrics, and matrix factorization.

Optimization in Machine Learning Log in to Mediaspace to watch this video

Explores optimization techniques, word embeddings, and recommendation systems in machine learning.

Recommender Systems: Overview and Methods Log in to Mediaspace to watch this video

Explores the evolution of recommenders, collaborative filtering, Netflix Prize, model training, and optimization techniques.

Recommender Systems: Matrix Factorization & Evaluation Log in to Mediaspace to watch this video

Explores matrix factorization techniques for recommender systems, including evaluation metrics like RMSE and NDCG.

Projects Presentation & Logistics Log in to Mediaspace to watch this video

Covers the presentation of 4 projects in the course and related logistics.