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  • A Practitioner's Approach
    Tayyaba Azim; Sarah Ahmed
    978-3-319-98524-4
    2018
    Edition 1
    • Presents a step-by-step approach to deriving a kernel from any probabilistic model belonging to the family of deep networks
    • Demonstrates the use of feature compression and selection techniques for reducing the dimensionality of Fisher vectors
    • Reviews efficient algorithms for large-scale image retrieval and classification systems, including concrete examples on different datasets
    • Provides programming solutions to help machine learning practitioners develop scalable solutions with novel ideas

    €100

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