NBML Course

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m (Neural Networks)
m (The Fundamentals: Basic Math and Machine Learning Theory)
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=== Curriculum ===
 
=== Curriculum ===
  
==== The Fundamentals: Basic Math and Machine Learning Theory ====
+
==== The Fundamentals: Basic Math ====
 
*[[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]]
 
**[[Machine_Learning/NBML/Linear Algebra/Vectors and Matricies|Vectors and Matricies]]
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***[[Machine_Learning/NBML/Probability/Information Theory/Entropy|Entropy]]
 
***[[Machine_Learning/NBML/Probability/Information Theory/Entropy|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]]
+
 
**[[Machine_Learning/NBML/Machine Learning/Data|The data]]
+
==== [[Machine_Learning/NBML/Machine Learning|Machine Learning]] ====
**[[Machine_Learning/NBML/Machine Learning/Model|The model]]
+
*[[Machine_Learning/NBML/Machine Learning/Data|The data]]
***[[Machine_Learning/NBML/Machine Learning/Model/Discriminative vs Generative|Discriminative vs Generative Models]]
+
*[[Machine_Learning/NBML/Machine Learning/Model|The model]]
**[[Machine_Learning/NBML/Machine Learning/Learning|Unsupervised vs. Supervised Learning]]
+
**[[Machine_Learning/NBML/Machine Learning/Model/Discriminative vs Generative|Discriminative vs Generative Models]]
**[[Machine_Learning/NBML/Machine Learning/Training|Training a Model]]
+
*[[Machine_Learning/NBML/Machine Learning/Learning|Unsupervised vs. Supervised Learning]]
***[[Machine_Learning/NBML/Machine Learning/Maximum Likelihood|Maximum Likelihood]]
+
*[[Machine_Learning/NBML/Machine Learning/Training|Training a Model]]
***[[Machine_Learning/NBML/Machine Learning/Optimization|Optimization]]
+
**[[Machine_Learning/NBML/Machine Learning/Maximum Likelihood|Maximum Likelihood]]
****[[Machine_Learning/NBML/Machine Learning/Optimization/Gradient Descent|Gradient Descent]]
+
**[[Machine_Learning/NBML/Machine Learning/Optimization|Optimization]]
****[[Machine_Learning/NBML/Machine Learning/Optimization/Lagrange Optimization|Lagrange Optimization]]
+
***[[Machine_Learning/NBML/Machine Learning/Optimization/Gradient Descent|Gradient Descent]]
****[[Machine_Learning/NBML/Machine Learning/Optimization/Expectation-Maximization|Expectation Maxmimization]]
+
***[[Machine_Learning/NBML/Machine Learning/Optimization/Lagrange Optimization|Lagrange Optimization]]
***[[Machine_Learning/NBML/Machine Learning/Regularization|Overfitting and Regularization]]
+
***[[Machine_Learning/NBML/Machine Learning/Optimization/Expectation-Maximization|Expectation Maxmimization]]
***[[Machine_Learning/NBML/Machine Learning/Bias-variance Tradeoff|Bias-Variance Tradeoff]]
+
**[[Machine_Learning/NBML/Machine Learning/Regularization|Overfitting and Regularization]]
 +
**[[Machine_Learning/NBML/Machine Learning/Bias-variance Tradeoff|Bias-Variance Tradeoff]]
  
 
==== [[Machine_Learning/NBML/Linear Regression|Linear Regression]] ====
 
==== [[Machine_Learning/NBML/Linear Regression|Linear Regression]] ====

Revision as of 10:02, 6 January 2011

Contents

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

Machine Learning

Linear Regression

Linear Classification

Generalized Linear Models

Support Vector Machines

Neural Networks

Clustering and Dimensional Reduction

Graphical Models

Hidden Markov Models

Personal tools