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Introduction to Machine Learning
This video was recorded at PASCAL Bootcamp in Machine Learning, Marseille 2010. How can we represent data on a computer and use it to learn to perform useful tasks? This lecture reviews some simple classification and regression rules, discusses under- and over-fitting and emphasises the utility of defining objective functions for learning. There is also a short overview of Bayesian learning, and some practical tips for pre-processing and visualizing data. The lecture ends with a brief mention of unsupervised learning and related topics.
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This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States
