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    Machine Learning practice session (29.04)

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    Klipi teostus: Mirjam Paales, Sven Laur 29.04.2013 3795 vaatamist Arvutiteadus


    XII. Principal component analysis

    Given by Sven Laur

    Home exercises to the XII session
    PCA analysis task
    PCA notes
    Materials for the exercise session
    Data for image analysis
    Session transcript Δ
    Deadline: May 6

    Seotud videod

    Machine Learning - Ia. Introduction to the course
    12.02.13
    Machine Learning - practice session (18.02)
    18.02.13
    Machine Learning - Linear models and polynomial interpolation
    19.02.13
    Machine Learning - practice session (25.02)
    25.02.13
    Machine Learning - Performance evaluation measures
    26.02.13
    Machine Learning - Introduction to optimization
    05.03.13
    Machine Learning - practice session (11.03)
    11.03.13
    Machine Learning - Linear Classification
    12.03.13
    Machine Learning - practice session (18.03)
    18.03.13
    Machine Learning - Feed-forward neural networks for prediction tasks
    19.03.13
    Machine Learning - practice session (25.03)
    25.03.13
    Machine Learning - Basics of probabilistic modelling
    26.03.13
    Machine Learning practice session (1.04)
    01.04.13
    Machine Learning - Maximum likelihood and maximum a posteriori estimates
    02.04.13
    Machine Learning practice session (8.04)
    08.04.13
    Machine Learning - Model-based clustering techniques
    09.04.13
    Machine Learning - practice session (15.04)
    15.04.13
    Machine Learning - Expectation-maximisation and data augmentation algorithms
    16.04.13
    Machine Learning practice session (22.04)
    22.04.13
    Machine Learning - Principal Component Analysis
    23.04.13
    Machine Learning - Statistical learning theory
    30.04.13
    Machine Learning practice session (6.05)
    06.05.13
    Machine Learning - Support Vector Machines
    07.05.13
    Machine Learning - Kernel Methods
    14.05.13
    Machine Learning practice session (21.05)
    20.05.13
    Machine Learning - Basics of ensemble methods
    21.05.13
    Machine Learning - Particle filters
    28.05.13