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  3. Machine Learning II (LTAT.02.004)
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Machine Learning II 2021/22 spring

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Homework points

  • Please follow requirements to home exercises!
  • The nominal score for each homework is 5 points.
  • You can score up to 7.5 points from each homework.
  • There are no restrictions how you choose exercises.

Homeworks

  • I. Performance measures
    • Deadline: 4th of March
1. Performance estimation
Solutions for this task can no longer be submitted.
  • II. Basics of probabilistic modelling
    • Deadline: 18th of March
2. Basics of probabilistic modelling
Solutions for this task can no longer be submitted.
  • III. Sequence models and belief propagation
    • Deadline: 8th of April
3. Sequence models and belief propagation
Solutions for this task can no longer be submitted.
  • IV. Direct applications of normal distributions
    • Deadline: 29th of April
    • Maximal score: 10 points
4. Direct application of normal distributions
Solutions for this task can no longer be submitted.
  • V. Normal distributions and affine projections
    • Deadline: 13th of May
5. Normal distributions and affine projections
Solutions for this task can no longer be submitted.
  • VI. Model-based clustering
    • Deadline: 30 may
6. Model-based clustering
Solutions for this task can no longer be submitted.
  • VII. Expectation-Maximisation algorithm
    • Deadline: 6 June
7. Expectation-maximisation
Solutions for this task can no longer be submitted.
  • VIII. Expectation-Maximisation algorithm and sequential data
    • Deadline:
Solutions for this task can not be submitted at the moment.
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  • Faculty of Science and Technology
  • University of Tartu
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