NBML Course: Difference between revisions

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**[[Machine_Learning/NBML/Probability/Information Theory|Information Theory]]
**[[Machine_Learning/NBML/Probability/Information Theory|Information Theory]]
***[[Machine_Learning/NBML/Probability/Information Theory/Entropy|Entropy]]
***[[Machine_Learning/NBML/Probability/Information Theory/Entropy|Entropy]]
***[[Machine_Learning/NBML/Probability/Information Theory/Relative Entropy|Relative Entropy]]
***[[Machine_Learning/NBML/Probability/Information Theory/Mutual Information|Mutual Information]]
***[[Machine_Learning/NBML/Probability/Information Theory/Mutual Information|Mutual Information]]
*[[Machine_Learning/NBML/Geometry for Computer Vision and Simulated Environments |Geometry for Computer Vision and Simulated Environments]]
*[[Machine_Learning/NBML/Geometry for Computer Vision and Simulated Environments |Geometry for Computer Vision and Simulated Environments]]
*[[Machine_Learning/NBML/Logic and Set Theory|Logic and Set Theory]]
*[[Machine_Learning/NBML/Logic and Set Theory|Logic and Set Theory]]
**[[Machine_Learning/NBML/Logic and Set Theory/Fuzzy Logic and Control Theory |Fuzzy Logic and Control Theory]]
**[[Machine_Learning/NBML/Logic and Set Theory/Fuzzy Logic and Control Theory |Fuzzy Logic and Control Theory]]

Latest revision as of 19:47, 16 April 2011

Noisebridge Machine Learning Course[edit]

We're trying to come up with a hands-on curriculum for teaching Machine Learning at Noisebridge. Please help out in any way you can, such as:

  1. Volunteer to teach a course in one of the subjects below
  2. Fill in one of the subjects below with links to learning material and related software
  3. Show up to classes and ask questions
  4. Join the ML Mailing List and talk about stuff
  5. Don't talk shit on mathematics - it wants to be your friend!

Online Machine Learning Courses[edit]

Curriculum[edit]

Machine Learning[edit]

Linear Regression[edit]

Linear Classification[edit]

Generalized Linear Models[edit]

Gaussian Process[edit]

Support Vector Machines[edit]

Neural Networks[edit]

Clustering and Dimensional Reduction[edit]

Graphical Models[edit]

Hidden Markov Models[edit]

Other Perspectives[edit]

The Fundamentals: Basic Math[edit]

Note: it's not essential to understand everything in this section! But the more you learn, the more things will make sense. Wikipedia is your friend.