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    LM101-047: How Build a Support Vector Machine to Classify Patterns (Rerun)

    LM101-047: How Build a Support Vector Machine to Classify Patterns (Rerun)

    FromLearning Machines 101

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    LM101-047: How Build a Support Vector Machine to Classify Patterns (Rerun)

    FromLearning Machines 101

    ratings:
    Length:
    35 minutes
    Released:
    Mar 14, 2016
    Format:
    Podcast episode

    Description

    We explain how to estimate the parameters of such machines to classify a pattern vector as a member of one of two categories as well as identify special pattern vectors called “support vectors” which are important for characterizing the Support Vector Machine decision boundary. The relationship of Support Vector Machine parameter estimation and logistic regression parameter estimation is also discussed.For more information..check us out at: www.learningmachines101.com
    also check us out on twitter at: lm101talk
     
    Released:
    Mar 14, 2016
    Format:
    Podcast episode

    Titles in the series (85)

    Smart machines based upon the principles of artificial intelligence and machine learning are now prevalent in our everyday life. For example, artificially intelligent systems recognize our voices, sort our pictures, make purchasing suggestions, and can automatically fly planes and drive cars. In this podcast series, we examine such questions such as: How do these devices work? Where do they come from? And how can we make them even smarter and more human-like? These are the questions which will be addressed in the podcast series Learning Machines 101.