NBML Course: Difference between revisions

From Noisebridge
Jump to navigation Jump to search
Line 62: Line 62:
*[[Machine_Learning/NBML/Linear Classification/Logistic|Logistic Regression]]
*[[Machine_Learning/NBML/Linear Classification/Logistic|Logistic Regression]]
*[[Machine_Learning/NBML/Linear Classification/Probit|Probit Regression]]
*[[Machine_Learning/NBML/Linear Classification/Probit|Probit Regression]]
==== [[Machine_Learning/NBML/GLM|Generalized Linear Models]] ====
==== [[Machine_Learning/NBML/GLM|Generalized Linear Models]] ====
==== [[Machine_Learning/NBML/SVM|Support Vector Machines]] ====
==== [[Machine_Learning/NBML/Neural Networks|Neural Networks ====
*[[Machine_Learning/NBML/Neural Networks/Feedforward|Feedforward Nets]]
*[[Machine_Learning/NBML/Neural Networks/Hopfield|Hopfield Nets/Autoassociators]]
*[[Machine_Learning/NBML/Neural Networks/Recurrent|Recurrent Neural Nets/Boltzmann Machines]]
==== [[Machine_Learning/NBML/Clustering|Clustering and Dimensional Reduction]] ====
*[[Machine_Learning/NBML/Clustering/KMeans|K-Means Clustering]]
*[[Machine_Learning/NBML/Clustering/PCA|Principle Component Analysis]]
*[[Machine_Learning/NBML/Clustering/ICA|Independent Component Analysis]]
==== [[Machine_Learning/NBML/Graphical Models|Graphical Models]] ====
*[[Machine_Learning/NBML/Graphical Models/Bayesian|Bayesian Networks]]
*[[Machine_Learning/NBML/Graphical Models/Markov Random Fields|Markov Random Fields]]
==== [[Machine_Learning/NBML/HMM|Hidden Markov Models]] ====

Revision as of 01:39, 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 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

Curriculum

The Fundamentals: Basic Math and Machine Learning Theory

Linear Regression

Linear Classification

Generalized Linear Models

Support Vector Machines

[[Machine_Learning/NBML/Neural Networks|Neural Networks

Clustering and Dimensional Reduction

Graphical Models

Hidden Markov Models