Recommender Systems

93 lessons in AI Fundamentals

• Popularity-Based Baseline RecommendersSlides / Video
• Popularity Bias and Filter BubblesSlides / Video
• Diversity, Novelty, and SerendipitySlides / Video
• Ranking vs Rating PredictionSlides / Video
• Evaluation Metrics for RecommendersSlides / Video
• Sparsity and Scalability ChallengesSlides / Video
• The Cold Start ProblemSlides / Video
• Hybrid Recommender SystemsSlides / Video
• Matrix Factorization and Latent FactorsSlides / Video
• Similarity Measures: Cosine and PearsonSlides / Video
• Explicit vs Implicit FeedbackSlides / Video
• The User-Item Interaction MatrixSlides / Video
• User-Based vs Item-Based FilteringSlides / Video
• What a Recommender System IsSlides / Video
• Collaborative Filtering OverviewSlides / Video
• Content-Based Filtering BasicsSlides / Video
• Real-World Applications of Recommender SystemsSlides / Video
• Building an Implicit Feedback MatrixCode Quiz
• Building a CSR Sparse MatrixCode Quiz
• Precision@K DenominatorCode Quiz
• Average Precision Rank IndexCode Quiz
• DCG Log DiscountCode Quiz
• Recall@K DenominatorCode Quiz
• Catalog Coverage DenominatorCode Quiz
• Weighted Hybrid Score BlendCode Quiz
• Ranking vs Rating PredictionQuiz
• Knowledge-Based RecommendationsQuiz
• Hybrid Recommender SystemsQuiz
• Collaborative Filtering OverviewQuiz
• Neighborhood vs Model-Based MethodsQuiz
• Scalability in RecommendersQuiz
• Popularity-Based BaselinesQuiz
• Ranking Metrics (NDCG, MAP, MRR)Quiz
• Similarity Measures (Cosine, Pearson)Quiz
• Explicit vs Implicit FeedbackQuiz
• Content-Based FilteringQuiz
• The Cold-Start ProblemQuiz
• Diversity, Novelty, and SerendipityQuiz
• Evaluating Recommenders (Precision@K, Recall@K)Quiz
• User-Item Interaction MatrixQuiz
• Item-Based Collaborative FilteringQuiz
• Filter Bubbles and Feedback LoopsQuiz
• User-Based Collaborative FilteringQuiz
• Matrix Factorization for RecommendationsQuiz
• Candidate Generation and Ranking StagesQuiz
• Latent Factors in RecommendationsQuiz
• Offline vs Online EvaluationQuiz
• Context-Aware RecommendationsQuiz
• What a Recommender System IsQuiz
• Data Sparsity ChallengeQuiz
• Deep Learning for RecommendationsQuiz
• BPR Ranking Loss DirectionCode Quiz
• Missing vs Zero Ratings in AverageCode Quiz
• Building a User ProfileCode Quiz
• Filtering Already-Seen ItemsCode Quiz
• Top-N Recommendation RankingCode Quiz
• Content-Based Cosine SimilarityCode Quiz
• Bias Terms in MF PredictionCode Quiz
• Regularization in Matrix FactorizationCode Quiz
• Popularity-Based BaselineCode Quiz
• Cold-Start Fallback LogicCode Quiz
• SGD Update for Latent FactorsCode Quiz
• Matrix Factorization PredictionCode Quiz
• Weighted Rating AggregationCode Quiz
• Mean-Centering RatingsCode Quiz
• Selecting the K Nearest NeighborsCode Quiz
• Item-Based CF PredictionCode Quiz
• User-Based CF PredictionCode Quiz
• Building the User-Item MatrixCode Quiz
• Real-World Applications of RecommendersFlashcard
• Context-Aware and Session-Based RecommendationsFlashcard
• Popularity-Based / Baseline RecommendersFlashcard
• Precision@K and Recall@KFlashcard
• Filter Bubbles and Feedback LoopsFlashcard
• Neighborhood-Based MethodsFlashcard
• Scalability Challenges in RecommendersFlashcard
• Ranking Metrics: NDCG, MAP, MRRFlashcard
• Deep Learning-Based RecommendersFlashcard
• Candidate Generation vs RankingFlashcard
• Diversity, Novelty, and SerendipityFlashcard
• Similarity Measures for RecommendationsFlashcard
• Cold Start ProblemFlashcard
• Matrix FactorizationFlashcard
• Data Sparsity in RecommendersFlashcard
• Latent Factors and EmbeddingsFlashcard
• User-Item Interaction MatrixFlashcard
• Hybrid Recommender SystemsFlashcard
• Item-Based Collaborative FilteringFlashcard
• Collaborative Filtering OverviewFlashcard
• What is a Recommender SystemFlashcard
• Explicit vs Implicit FeedbackFlashcard
• User-Based Collaborative FilteringFlashcard
• Content-Based FilteringFlashcard