NBML Course: Difference between revisions
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==== [[Machine_Learning/NBML/GLM|Generalized Linear Models]] ==== | ==== [[Machine_Learning/NBML/GLM|Generalized Linear Models]] ==== | ||
==== [[Machine_Learning/NBML/GP|Gaussian Process]] ==== | |||
==== [[Machine_Learning/NBML/SVM|Support Vector Machines]] ==== | ==== [[Machine_Learning/NBML/SVM|Support Vector Machines]] ==== | ||
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*[[Machine_Learning/NBML/Clustering/PCA|Principle Component Analysis]] | *[[Machine_Learning/NBML/Clustering/PCA|Principle Component Analysis]] | ||
*[[Machine_Learning/NBML/Clustering/ICA|Independent Component Analysis]] | *[[Machine_Learning/NBML/Clustering/ICA|Independent Component Analysis]] | ||
*[[Machine_Learning/NBML/Clustering/Dimensional Reduction for Visualization|Dimensional Reduction and Clustering for Visualization]] | |||
**[[Machine_Learning/NBML/Clustering/Dimensional Reduction for Visualization/Self Organizing Map (algebraic perspective) | Self Organizing Map (algebraic perspective)]] | |||
**[[Machine_Learning/NBML/Clustering/Dimensional Reduction for Visualization/Supervised Methods and Refinement (LVQ)|Supervised Methods and Refinement (LVQ)]] | |||
*[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text |Clustering Techniques for Text Collections]] | |||
**[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text/Spherical K-Means |Spherical K-Means]] | |||
**[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text/Word Sense Disambiguation (Sense Clusters)|Word Sense Disambiguation (Sense Clusters)]] | |||
**[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text/Latent Semantic Indexing (LSI)|Latent Semantic Indexing (LSI)]] | |||
***[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text/Latent Semantic Indexing (LSI)/Keyword Relatedness Clustering (Semantic Engine)|Keyword Relatedness Clustering (Semantic Engine)]] | |||
**[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text/Text Clustering with Self Organizing Map (WebSOM)|Text Clustering with Self Organizing Map (WebSOM)]] | |||
==== [[Machine_Learning/NBML/Graphical Models|Graphical Models]] ==== | ==== [[Machine_Learning/NBML/Graphical Models|Graphical Models]] ==== | ||
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==== [[Machine_Learning/NBML/HMM|Hidden Markov Models]] ==== | ==== [[Machine_Learning/NBML/HMM|Hidden Markov Models]] ==== | ||
==== [[ Other Perspectives | Other Perspectives]] ==== | |||
*[[Machine_Learning/Linguistics and The Role of Language | Linguistics and The Role of Language]] | |||
**[[Machine_Learning/Symbolic Methods and Machine Understanding |Symbolic Methods and Machine Understanding]] | |||
*[[Machine_Learning/Simulation and Integrated Software Systems |Simulation and Integrated Software Systems]] | |||
**[[Machine_Learning/Autonomous Agents and Evolutionary (Learning) Algorithms |Autonomous Agents and Evolutionary (Learning) Algorithms]] | |||
==== The Fundamentals: Basic Math ==== | ==== The Fundamentals: Basic Math ==== | ||
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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:
- 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[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]
- K-Means Clustering
- Principle Component Analysis
- Independent Component Analysis
- Dimensional Reduction and Clustering for Visualization
- Clustering Techniques for Text Collections
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.