Top: Computer Science: Machine Learning:

Description

As a broad subfield of artificial intelligence, machine learning is concerned with the development of algorithms and techniques that allow computers to "learn". At a general level, there are two types of learning: inductive, and deductive. Inductive machine learning methods extract rules and patterns out of massive data sets. Some parts of machine learning are closely related to data mining and statistics. Machine learning research is focused on the computational properties of the statistical methods, such as their computational complexity. Machine learning has a wide spectrum of applications including natural language processing,syntactic pattern recognition, search engines, medical diagnosis, bioinformatics and cheminformatics, detecting credit card fraud, stock market analysis, classifying DNA sequences, speech and handwriting recognition, object recognition in computer vision, game playing and robot locomotion.
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Subcategories

Boosting (7)
Clustering (57)
Regression (3)

Lectures
Joaquin Quiñonero Candela, Colin de la Higuera, Isabelle Guyon, José Balcázar, Mark Girolami, Mikaela Keller, Ulrike von Luxburg
Nicolò Cesa-Bianchi
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