# NBML Course

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==== [[Machine_Learning/NBML/GLM|Generalized Linear Models]] ==== | ==== [[Machine_Learning/NBML/GLM|Generalized Linear Models]] ==== | ||

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+ | ==== [[Machine_Learning/NBML/GP|Gaussian Process]] ==== | ||

==== [[Machine_Learning/NBML/SVM|Support Vector Machines]] ==== | ==== [[Machine_Learning/NBML/SVM|Support Vector Machines]] ==== |

## Revision as of 00:09, 16 February 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:

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

### Online Machine Learning Courses

### Curriculum

#### Machine Learning

#### Linear Regression

#### Linear Classification

#### Generalized Linear Models

#### Gaussian Process

#### Support Vector Machines

#### Neural Networks

#### Clustering and Dimensional Reduction

- K-Means Clustering
- Principle Component Analysis
- Independent Component Analysis
- Dimensional Reduction and Clustering for Visualization
- Clustering Techniques for Text Collections

#### Graphical Models

#### Hidden Markov Models

#### Other Perspectives

#### The Fundamentals: Basic Math

*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. *