Concept

Similarity measure

Related lectures (16)

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

Advanced Structure Discovery: Distance Metrics and Time Series Data

Explores clustering algorithms, distance metrics, and time series data analysis techniques.

Data Summarization: Minhashing and Locality-Sensitive Hashing

Explores Jaccard similarity, minhashing, and locality-sensitive hashing for data summarization.

Data Compression: Privacy-Preserving Techniques

Explores privacy-preserving data management and data summarization techniques for finding similar items.

Entity Resolution Techniques

Explores entity resolution techniques, data deduplication, similarity metrics, computational cost, blocking techniques, and scaling out similarity joins.

Information Retrieval Basics: Overview and Text-Based Retrieval

Covers the basics of information retrieval, including text-based retrieval and indexing techniques.

Near Neighbors Retrieval: Efficient Techniques

Covers techniques for efficiently retrieving similar items using similarity search queries.

Classification by Similarity

Delves into classification by similarity using prototypes to match noisy images.

Data Streams: Algorithms and Applications

Covers data streams, sub-linear memory computation, document similarity, and randomized dimension reduction techniques for handling 'Big Data' challenges efficiently.

Recommender Systems: Overview and Methods

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

Introduction to Information Retrieval

Introduces the basics of information retrieval, covering text-based retrieval, document features, similarity functions, and the difference between Boolean and ranked retrieval.

Digital Image Correlation

Covers digital image correlation, similarity criteria, iterative approaches, and practical applications in 2D and 3D correlation.

Recommender Systems: Part 1

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

Information Retrieval Basics

Introduces the basics of information retrieval, covering text-based and Boolean retrieval, vector space retrieval, and similarity computation.

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