NBML Course

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(The Fundamentals: Basic Math)
 
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#Volunteer to teach a course in one of the subjects below
 
#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
 
#Fill in one of the subjects below with links to learning material and related software
#Show up to classes and asking questions
+
#Show up to classes and ask questions
 
#Join the [https://www.noisebridge.net/mailman/listinfo/ml ML Mailing List] and talk about stuff
 
#Join the [https://www.noisebridge.net/mailman/listinfo/ml ML Mailing List] and talk about stuff
 
#Don't talk shit on mathematics - it wants to be your friend!
 
#Don't talk shit on mathematics - it wants to be your friend!
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=== Curriculum ===
 
=== Curriculum ===
  
==== The Fundamentals: Basic Math and Machine Learning Theory ====
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==== [[Machine_Learning/NBML/Machine Learning|Machine Learning]] ====
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*[[Machine_Learning/NBML/Machine Learning/Data|The data]]
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*[[Machine_Learning/NBML/Machine Learning/Model|The model]]
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**[[Machine_Learning/NBML/Machine Learning/Model/Discriminative vs Generative|Discriminative vs Generative Models]]
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*[[Machine_Learning/NBML/Machine Learning/Learning|Unsupervised vs. Supervised Learning]]
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*[[Machine_Learning/NBML/Machine Learning/Training|Training a Model]]
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**[[Machine_Learning/NBML/Machine Learning/Maximum Likelihood|Maximum Likelihood]]
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**[[Machine_Learning/NBML/Machine Learning/Optimization|Optimization]]
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***[[Machine_Learning/NBML/Machine Learning/Optimization/Gradient Descent|Gradient Descent]]
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***[[Machine_Learning/NBML/Machine Learning/Optimization/Lagrange Optimization|Lagrange Optimization]]
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***[[Machine_Learning/NBML/Machine Learning/Optimization/Expectation-Maximization|Expectation Maxmimization]]
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**[[Machine_Learning/NBML/Machine Learning/Regularization|Overfitting and Regularization]]
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**[[Machine_Learning/NBML/Machine Learning/Bias-variance Tradeoff|Bias-Variance Tradeoff]]
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==== [[Machine_Learning/NBML/Linear Regression|Linear Regression]] ====
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*[[Machine_Learning/NBML/Linear Regression/Least Squares|Least Squares Formulation]]
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*[[Machine_Learning/NBML/Linear Regression/Maximum Likelihood| Maximum Likelihood Formulation]]
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*[[Machine_Learning/NBML/Linear Regression/Regularization|Regularization]]
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**[[Machine_Learning/NBML/Linear Regression/Ridge|Ridge Regression (L2)]]
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**[[Machine_Learning/NBML/Linear Regression/Lasso|Lasso Regression (L1)]]
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**[[Machine_Learning/NBML/Linear Regression/LARS|Least-angle/Elastic Net Regression]]
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*[[Machine_Learning/NBML/Linear Regression/Bayesian|Bayesian Linear Regression]]
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==== [[Machine_Learning/NBML/Linear Classification|Linear Classification]] ====
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*[[Machine_Learning/NBML/Linear Classification/Fishers Discriminant|Fisher's Linear Discriminant]]
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*[[Machine_Learning/NBML/Linear Classification/Logistic|Logistic Regression]]
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*[[Machine_Learning/NBML/Linear Classification/Probit|Probit Regression]]
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==== [[Machine_Learning/NBML/GLM|Generalized Linear Models]] ====
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==== [[Machine_Learning/NBML/GP|Gaussian Process]] ====
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==== [[Machine_Learning/NBML/SVM|Support Vector Machines]] ====
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==== [[Machine_Learning/NBML/Neural Networks|Neural Networks]] ====
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*[[Machine_Learning/NBML/Neural Networks/Feedforward|Feedforward Nets]]
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*[[Machine_Learning/NBML/Neural Networks/Hopfield|Hopfield Nets/Autoassociators]]
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*[[Machine_Learning/NBML/Neural Networks/Recurrent|Recurrent Nets/Boltzmann Machines]]
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*[[Machine_Learning/NBML/Neural Networks/Deep Belief|Deep Belief Nets]]
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==== [[Machine_Learning/NBML/Clustering|Clustering and Dimensional Reduction]] ====
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*[[Machine_Learning/NBML/Clustering/KMeans|K-Means Clustering]]
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*[[Machine_Learning/NBML/Clustering/PCA|Principle Component Analysis]]
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*[[Machine_Learning/NBML/Clustering/ICA|Independent Component Analysis]]
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*[[Machine_Learning/NBML/Clustering/Dimensional Reduction for Visualization|Dimensional Reduction and Clustering for Visualization]]
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**[[Machine_Learning/NBML/Clustering/Dimensional Reduction for Visualization/Self Organizing Map (algebraic perspective) | Self Organizing Map (algebraic perspective)]]
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**[[Machine_Learning/NBML/Clustering/Dimensional Reduction for Visualization/Supervised Methods and Refinement (LVQ)|Supervised Methods and Refinement (LVQ)]]
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*[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text |Clustering Techniques for Text Collections]]
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**[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text/Spherical K-Means |Spherical K-Means]]
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**[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text/Word Sense Disambiguation (Sense Clusters)|Word Sense Disambiguation (Sense Clusters)]]
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**[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text/Latent Semantic Indexing (LSI)|Latent Semantic Indexing (LSI)]]
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***[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text/Latent Semantic Indexing (LSI)/Keyword Relatedness Clustering (Semantic Engine)|Keyword Relatedness Clustering (Semantic Engine)]]
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**[[Machine_Learning/NBML/Clustering/Clustering Techniques for Text/Text Clustering with Self Organizing Map (WebSOM)|Text Clustering with Self Organizing Map (WebSOM)]]
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==== [[Machine_Learning/NBML/Graphical Models|Graphical Models]] ====
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*[[Machine_Learning/NBML/Graphical Models/Bayesian|Bayesian Networks]]
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*[[Machine_Learning/NBML/Graphical Models/Markov Random Fields|Markov Random Fields]]
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==== [[Machine_Learning/NBML/HMM|Hidden Markov Models]] ====
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==== [[ Other Perspectives | Other Perspectives]] ====
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*[[Machine_Learning/Linguistics and The Role of Language | Linguistics and The Role of Language]]
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**[[Machine_Learning/Symbolic Methods and Machine Understanding |Symbolic Methods and Machine Understanding]]
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*[[Machine_Learning/Simulation and Integrated Software Systems |Simulation and Integrated Software Systems]]
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**[[Machine_Learning/Autonomous Agents and Evolutionary (Learning) Algorithms |Autonomous Agents and Evolutionary (Learning) Algorithms]]
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==== The Fundamentals: Basic Math ====
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''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. ''
 
*[[Machine_Learning/NBML/Linear Algebra|Linear Algebra]]
 
*[[Machine_Learning/NBML/Linear Algebra|Linear Algebra]]
**[[Machine_Learning/NBML/Linear Algebra/Vectors and Matricies|Vectors and Matricies]]
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**[[Machine_Learning/NBML/Linear Algebra/Vectors and Matrices|Vectors and Matrices]]
**[[Machine_Learning/NBML/Linear Algebra/Solving Linear Systems|Solving Linear Systems: Gaussian Elimination]]
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**[[Machine_Learning/NBML/Linear Algebra/Solving Linear Systems|Solving Linear Systems ]]
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***[[Machine_Learning/NBML/Linear Algebra/Solving Linear Systems/LU Decomposition |LU Decomposition]]
 
**[[Machine_Learning/NBML/Linear Algebra/Vector Spaces|Vector Spaces]]
 
**[[Machine_Learning/NBML/Linear Algebra/Vector Spaces|Vector Spaces]]
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**[[Machine_Learning/NBML/Linear Algebra/Vector Spaces/Orthogonalization algorithms|Orthogonalization algorithms]]
 
**[[Machine_Learning/NBML/Linear Algebra/Eigenvectors and Eigenvalues|Eigenvectors and Eigenvalues]]
 
**[[Machine_Learning/NBML/Linear Algebra/Eigenvectors and Eigenvalues|Eigenvectors and Eigenvalues]]
 
**[[Machine_Learning/NBML/Linear Algebra/Quadratic Forms|Quadratic Forms]]
 
**[[Machine_Learning/NBML/Linear Algebra/Quadratic Forms|Quadratic Forms]]
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**[[Machine_Learning/NBML/Linear Algebra/Singular Value Decomposition (SVD) |Singular Value Decompostion (SVD)]]
 
*[[Machine_Learning/NBML/Calculus|Calculus]]
 
*[[Machine_Learning/NBML/Calculus|Calculus]]
 
**[[Machine_Learning/NBML/Calculus/Derivatives, Gradients, and Hessians|Derivatives, Gradients, and Hessians]]
 
**[[Machine_Learning/NBML/Calculus/Derivatives, Gradients, and Hessians|Derivatives, Gradients, and Hessians]]
 
**[[Machine_Learning/NBML/Calculus/Integration|Integration]]
 
**[[Machine_Learning/NBML/Calculus/Integration|Integration]]
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**[[Machine_Learning/NBML/Calculus/Fourier Transform | Fourier Transform]]
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**[[Machine_Learning/NBML/Calculus/Vector Calculus | Vector Calculus]]
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***[[Machine_Learning/NBML/Calculus/Vector Calculus/Optimization, Duality, Lagrange Multipliers and Kuhn-Tucker Theorem |Optimization, Duality, Lagrange Multipliers and Kuhn-Tucker Theorem ]]
 
*[[Machine_Learning/NBML/Probability|Probability Theory]]
 
*[[Machine_Learning/NBML/Probability|Probability Theory]]
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**[[Machine_Learning/NBML/Probability/Basic Probability|Basic Probability]]
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***[[Machine_Learning/NBML/Probability/Basic Probability/Bayes Theorem | Bayes Theorem]]
 
**[[Machine_Learning/NBML/Probability/Distribution and Density Functions|Distribution and Density Functions]]
 
**[[Machine_Learning/NBML/Probability/Distribution and Density Functions|Distribution and Density Functions]]
 
***[[Machine_Learning/NBML/Probability/Distribution and Density Functions/Discrete Distributions|Discrete Distributions]]
 
***[[Machine_Learning/NBML/Probability/Distribution and Density Functions/Discrete Distributions|Discrete Distributions]]
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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]]
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***[[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/Machine Learning|Machine Learning]]
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*[[Machine_Learning/NBML/Geometry for Computer Vision and Simulated Environments |Geometry for Computer Vision and Simulated Environments]]
**[[Machine_Learning/NBML/Machine Learning/Data|The data]]
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*[[Machine_Learning/NBML/Logic and Set Theory|Logic and Set Theory]]
**[[Machine_Learning/NBML/Machine Learning/Model|The model]]
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**[[Machine_Learning/NBML/Logic and Set Theory/Fuzzy Logic and Control Theory |Fuzzy Logic and Control Theory]]
**[[Machine_Learning/NBML/Machine Learning/Learning|Unsupervised vs. Supervised Learning]]
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**[[Machine_Learning/NBML/Machine Learning/Training|Training a Model]]
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***[[Machine_Learning/NBML/Machine Learning/Maximum Likelihood|Maximum Likelihood]]
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***[[Machine_Learning/NBML/Machine Learning/Optimization|Optimization]]
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****[[Machine_Learning/NBML/Machine Learning/Optimization/Gradient Descent|Gradient Descent]]
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****[[Machine_Learning/NBML/Machine Learning/Optimization/Lagrange Optimization|Lagrange Optimization]]
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****[[Machine_Learning/NBML/Machine Learning/Optimization/Expectation-Maximization|Expectation Maxmimization]]
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***[[Machine_Learning/NBML/Machine Learning/Regularization|Overfitting and Regularization]]
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***[[Machine_Learning/NBML/Machine Learning/Bias-variance Tradeoff|Bias-Variance Tradeoff]]
+
 
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==== Linear Regression ====
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*[[Machine_Learning/NBML/Linear Regression|Linear Regression]]
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**[[Machine_Learning/NBML/Linear Regression/Least Squares|Least Squares Formulation]]
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**[[Machine_Learning/NBML/Linear Regression/Maximum Likelihood| Maximum Likelihood Formulation]]
+
**[[Machine_Learning/NBML/Linear Regression/Regularization|Regularization]]
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***[[Machine_Learning/NBML/Linear Regression/Ridge|Ridge Regression (L2)]]
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***[[Machine_Learning/NBML/Linear Regression/Lasso|Lasso Regression (L1)]]
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***[[Machine_Learning/NBML/Linear Regression/LARS|Least-angle/Elastic Net Regression]]
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**[[Machine_Learning/NBML/Linear Regression/Bayesian|Bayesian Linear Regression]]
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==== Block 3: Linear Classification (non-SVM) ====
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*Linear Classification
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**Binary vs. Multi-class
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***One-versus-the-rest, one-versus-one
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**Discriminant Functions
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Latest revision as of 19:47, 16 April 2011

Contents

[edit] 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!

[edit] 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

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.

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