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    LM101-060: How to Monitor Machine Learning Algorithms using Anomaly Detection Machine Learning Algorithms

    LM101-060: How to Monitor Machine Learning Algorithms using Anomaly Detection Machine Learning Algorithms

    FromLearning Machines 101

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    LM101-060: How to Monitor Machine Learning Algorithms using Anomaly Detection Machine Learning Algorithms

    FromLearning Machines 101

    ratings:
    Length:
    30 minutes
    Released:
    Jan 23, 2017
    Format:
    Podcast episode

    Description

    This 60th episode of Learning Machines 101 discusses how one can use novelty detection or anomaly detection machine learning algorithms to monitor the performance of other machine learning algorithms deployed in real world environments. The episode is based upon a review of a talk by Chief Data Scientist Ira Cohen of Anodot presented at the 2016 Berlin Buzzwords Data Science Conference. Check out: www.learningmachines101.com to hear the podcast or read a transcription of the podcast!
    Released:
    Jan 23, 2017
    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.