Current Time 0:00
Duration -:-
Loaded: 0%
Stream Type LIVE
Remaining Time -:-
 
1x
  • Chapters
  • descriptions off, selected
  • subtitles off, selected
    • Quality

    Machine Learning - practice session (11.03)

    Embed
    Klipi teostus: Mirjam Paales 11.03.2013 3713 vaatamist Haridusteadus


    V. Introduction to Optimization

    Given by Konstantin Tretyakov
    Exercises
    Deadline: March 18

     

    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 - 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 practice session (29.04)
    29.04.13
    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