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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 ask questions
#Show up to classes and asking 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.


=== Online Machine Learning Courses ===
=== Online Machine Learning Courses ===
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=== Curriculum ===
=== Curriculum ===


==== [[Machine_Learning/NBML/Machine Learning|Machine Learning]] ====
==== Block 1: Basic Math and Machine Learning ====
*[[Machine_Learning/NBML/Machine Learning/Data|The data]]
*Linear Algebra
*[[Machine_Learning/NBML/Machine Learning/Model|The model]]
**Vectors and Matricies
**[[Machine_Learning/NBML/Machine Learning/Model/Discriminative vs Generative|Discriminative vs Generative Models]]
**Solving Linear Systems: Gaussian Elimination
*[[Machine_Learning/NBML/Machine Learning/Learning|Unsupervised vs. Supervised Learning]]
**Vector Spaces
*[[Machine_Learning/NBML/Machine Learning/Training|Training a Model]]
**Eigenvectors and Eigenvalues
**[[Machine_Learning/NBML/Machine Learning/Maximum Likelihood|Maximum Likelihood]]
**Quadratic Forms
**[[Machine_Learning/NBML/Machine Learning/Optimization|Optimization]]
*Calculus
***[[Machine_Learning/NBML/Machine Learning/Optimization/Gradient Descent|Gradient Descent]]
**Derivatives, Gradients, and Hessians
***[[Machine_Learning/NBML/Machine Learning/Optimization/Lagrange Optimization|Lagrange Optimization]]
**Integration as Sums
***[[Machine_Learning/NBML/Machine Learning/Optimization/Expectation-Maximization|Expectation Maxmimization]]
*Probability Theory
**[[Machine_Learning/NBML/Machine Learning/Regularization|Overfitting and Regularization]]
**Distribution and Density Functions
**[[Machine_Learning/NBML/Machine Learning/Bias-variance Tradeoff|Bias-Variance Tradeoff]]
***Discrete Distributions
***Continuous Distributions
**Random Variables and Vectors
**Expectation
**Variance and Covariance
**Correlation Functions
**Law of Large Numbers
**Information Theory
***Entropy
***Mutual Information
*Machine Learning
**The data
**The model
**Unsupervised vs. Supervised Learning
**Training a Model
***Maximum Likelihood
***Optimization
****Gradient Descent
****Lagrange Optimization
***Expectation-Maximization
***Overfitting and Regularization
***Bias-variance Tradeoff


==== [[Machine_Learning/NBML/Linear Regression|Linear Regression]] ====
==== Block 2: Linear Regression and Classification ====
*[[Machine_Learning/NBML/Linear Regression/Least Squares|Least Squares Formulation]]
*Linear Regression
*[[Machine_Learning/NBML/Linear Regression/Maximum Likelihood| Maximum Likelihood Formulation]]
**Least Squares Formulation
*[[Machine_Learning/NBML/Linear Regression/Regularization|Regularization]]
**Maximum-likelihood Formulation
**[[Machine_Learning/NBML/Linear Regression/Ridge|Ridge Regression (L2)]]
**Regularization
**[[Machine_Learning/NBML/Linear Regression/Lasso|Lasso Regression (L1)]]
***Ridge Regression (L2)
**[[Machine_Learning/NBML/Linear Regression/LARS|Least-angle/Elastic Net Regression]]
***Lasso Regression (L1)
*[[Machine_Learning/NBML/Linear Regression/Bayesian|Bayesian Linear Regression]]
***Least-angle/Elastic Net Regression
 
**Bayesian Linear Regression
==== [[Machine_Learning/NBML/Linear Classification|Linear Classification]] ====
*Linear Classification
*[[Machine_Learning/NBML/Linear Classification/Fishers Discriminant|Fisher's Linear Discriminant]]
*[[Machine_Learning/NBML/Linear Classification/Logistic|Logistic Regression]]
*[[Machine_Learning/NBML/Linear Classification/Probit|Probit Regression]]
 
==== [[Machine_Learning/NBML/GLM|Generalized Linear Models]] ====
 
==== [[Machine_Learning/NBML/GP|Gaussian Process]] ====
 
==== [[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 Nets/Boltzmann Machines]]
*[[Machine_Learning/NBML/Neural Networks/Deep Belief|Deep Belief Nets]]
 
==== [[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/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/Bayesian|Bayesian Networks]]
*[[Machine_Learning/NBML/Graphical Models/Markov Random Fields|Markov Random Fields]]
 
==== [[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 ====
''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/Vectors and Matrices|Vectors and Matrices]]
**[[Machine_Learning/NBML/Linear Algebra/Solving Linear Systems|Solving Linear Systems ]]
***[[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/Orthogonalization algorithms|Orthogonalization algorithms]]
**[[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/Singular Value Decomposition (SVD) |Singular Value Decompostion (SVD)]]
*[[Machine_Learning/NBML/Calculus|Calculus]]
**[[Machine_Learning/NBML/Calculus/Derivatives, Gradients, and Hessians|Derivatives, Gradients, and Hessians]]
**[[Machine_Learning/NBML/Calculus/Integration|Integration]]
**[[Machine_Learning/NBML/Calculus/Fourier Transform | Fourier Transform]]
**[[Machine_Learning/NBML/Calculus/Vector Calculus | Vector Calculus]]
***[[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/Basic Probability|Basic Probability]]
***[[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/Discrete Distributions|Discrete Distributions]]
***[[Machine_Learning/NBML/Probability/Distribution and Density Functions/Continuous Distributions|Continuous Distributions]]
**[[Machine_Learning/NBML/Probability/Random Variables and Vectors|Random Variables and Vectors]]
**[[Machine_Learning/NBML/Probability/Expectation|Expectation]]
**[[Machine_Learning/NBML/Probability/Variance and Covariance|Variance and Covariance]]
**[[Machine_Learning/NBML/Probability/Correlation Functions|Correlation Functions]]
**[[Machine_Learning/NBML/Probability/Law of Large Numbers|Law of Large Numbers]]
**[[Machine_Learning/NBML/Probability/Information Theory|Information Theory]]
***[[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/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/Fuzzy Logic and Control Theory |Fuzzy Logic and Control Theory]]
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