Machine Learning
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CMU
Alex Smola
Barnabas Poczos
Ina Fiterau
Junier Oliva
Leila Wehbe
Mu Li
Xuezhi Wang
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CMU

Graphical Models

Introduction to Machine Learning - 10-701/15-781

Content

  • Application: Sprinkler, earthquake and burglar

  • Conditional probabilities

    • Joint distribution

    • Parameter estimation for fully observed models

  • Statistical model

    • Conditional independence

    • Effects of observing variables (explaining away etc.)

    • Causal implications

Supplementary material

Slides in PDF and Keynote coming soon. If you want to extract the equations from the slides you can do so by using LaTeXit, simply by dragging the equation images into it.

Videos

This is unedited video straight from a Lumix GF2 with a 20mm lens which should explain the sound (it doesn't have a dedicated audio input) … But it should help as a supplement with the slides (YouTube typically makes the 1080i version available within 1 week of the upload).