NBML Course

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(Block 2: Linear Regression)
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***[[Machine_Learning/NBML/Machine Learning/Bias-variance Tradeoff|Bias-Variance Tradeoff]]
***[[Machine_Learning/NBML/Machine Learning/Bias-variance Tradeoff|Bias-Variance Tradeoff]]
==== Block 2: Linear Regression ====
==== Linear Regression ====
*Linear Regression
*[[Machine_Learning/NBML/Linear Regression|Linear Regression]]
**Least Squares Formulation
**[[Machine_Learning/NBML/Linear Regression/Least Squares|Least Squares Formulation]]
**Maximum-likelihood Formulation
**[[Machine_Learning/NBML/Linear Regression/Maximum Likelihood| Maximum Likelihood Formulation]]
**[[Machine_Learning/NBML/Linear Regression/Regularization|Regularization]]
***Ridge Regression (L2)
***[[Machine_Learning/NBML/Linear Regression/Ridge|Ridge Regression (L2)]]
***Lasso Regression (L1)
***[[Machine_Learning/NBML/Linear Regression/Lasso|Lasso Regression (L1)]]
***Least-angle/Elastic Net Regression
***[[Machine_Learning/NBML/Linear Regression/LARS|Least-angle/Elastic Net Regression]]
**Bayesian Linear Regression
**[[Machine_Learning/NBML/Linear Regression/Bayesian|Bayesian Linear Regression]]
==== Block 3: Linear Classification (non-SVM) ====
==== Block 3: Linear Classification (non-SVM) ====

Revision as of 00:52, 6 January 2011


Noisebridge Machine Learning Course

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 asking 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


Block 1: Basic Math and Machine Learning

Linear Regression

Block 3: Linear Classification (non-SVM)

  • Linear Classification
    • Binary vs. Multi-class
      • One-versus-the-rest, one-versus-one
    • Discriminant Functions
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