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@mlatcl

ML at the Cambridge Computer Lab

ML@CL seeks to advance the safe and reliable deployment of machine learning systems to tackle the real-world challenges.

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  1. mlphysical mlphysical Public

    Machine Learning and the Physical World module

    HTML 28 7

  2. mlai mlai Public

    Machine learning and adaptive intelligence course

    HTML 9

  3. gpss gpss Public

    Talks from the Gaussian Process Summer School

    HTML 8 1

  4. deepnn deepnn Public

    Deep Neural Networks Module

    Jupyter Notebook 6 5

  5. fbp-vs-soa fbp-vs-soa Public

    Comparison of flow-based programming and service-oriented architecture for building data-driven applications

    Jupyter Notebook 6 2

  6. r255 r255 Public

    Lectures given in the department's Advanced Topics in Machine Learning

    HTML 4

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