Machine Learning

2010-05-06T03:11:34Z

Micahpearlman: /* Presentations and other Materials */

=== Next Meeting===

*When: Wednesday, 5/5/2010 @ 8:00pm
*Where: 2169 Mission St. (back corner classroom)
*Topic: A Brief Tour of Statistics
*Presenter: Thomas

=== Topics to Learn and Teach ===

*Supervised Learning
**Linear Regression (Mike S volunteered to teach)
**Linear Discriminants
**Neural Nets/Radial Basis Functions
**Support Vector Machines
**Classifier Combination [http://www.cedar.buffalo.edu/~srihari/CSE555/Chap9.Part6.pdf]
**A basic decision tree builder, recursive and using entropy metrics

*Unsupervised Learning
**Clustering/PCA
**k-Means Clustering
**Graphical Modeling
**Generative Models: gaussian distribution, multinomial distributions, HMMs, Naive Bayes

*Reinforcement Learning
**Temporal Difference Learning

*Math, Probability & Statistics
**Metric spaces and what they mean
**Fundamentals of probabilities
**Decision Theory (Bayesian)
**Maximum Likelihood
**Bias/Variance Tradeoff, VC Dimension
**Bagging, Bootstrap, Jacknife [http://www.cedar.buffalo.edu/~srihari/CSE555/Chap9.Part3.pdf]
**Information Theory: Entropy, Mutual Information, Gaussian Channels
**Estimation of Misclassification [http://www.cedar.buffalo.edu/~srihari/CSE555/Chap9.Part5.pdf]
**No-Free Lunch Theorem [http://www.cedar.buffalo.edu/~srihari/CSE555/Chap9.Part1.pdf]

*Machine Learning SDK's
** [http://opencv.willowgarage.com/documentation/index.html OpenCV] ML component (SVM, trees, etc)
**[http://lucene.apache.org/mahout/ Mahout] a Hadoop cluster based ML package.
**[http://www.cs.waikato.ac.nz/ml/weka/ Weka] a collection of data mining tools and machine learning algorithms.

*Applications
** Collective Intelligence & Recommendation Engines

=== Possible Projects ===

*[[KDD Competition 2010]]
*[[Online Optimization & Machine Learning Toolkit]]

=== Presentations and other Materials ===

* [[Awesome Machine Learning Applications]] -- A list of cool applications of ML
* [[Hands-on Machine Learning]], a presentation [[User:jbm|jbm]] gave on 2009-01-07.
* http://www.youtube.com/user/StanfordUniversity#g/c/A89DCFA6ADACE599 Stanford Machine Learning online course videos]

=== Notes from Meetings ===

[[Machine Learning Meetup Notes: 2010-04-28]] -- SVMs

[[Machine Learning Meetup Notes: 2010-04-21]] -- Linear Regression

[[Machine Learning Meetup Notes: 2010-04-14]] -- (re)Starting new Machine Learning Meetup!

[[Machine Learning Meetup Notes: 2009-04-01]] -- Finally moving on up: fully-connected backpropagation networks.

[[Machine Learning Meetup Notes: 2009-03-25]] -- We made perceptrons - added sigmoid, etc.

[[Machine Learning Meetup Notes: 2009-03-18]] -- We made perceptrons - linear function support!

[[Machine Learning Meetup Notes: 2009-03-11]] -- We made perceptrons!

Machine Learning Meetup Notes: 2009-03-04 -- Josh gave a presentation on SVMs

(time is missing!)

Machine Learning Meetup Notes: 2009-02-11 -- Josh gave a presentation on clustering, donuts!

Machine Learning Meetup Notes: 2009-02-04 -- Free-form hang out night, punch and pie

Machine Learning Meetup Notes: 2009-01-28 -- Praveen talked about Neural networks

Machine Learning Meetup Notes: 2008-01-21 -- Jean gave a quick overview of machine learning stuff

Machine Learning Meetup Notes: 2009-01-14 -- Ian gave a talk on k-Nearest Neighbor

Machine Learning Meetup Notes: 2009-01-07 -- Josh did a quick intro to ML presentation

[[Machine Learning Meetup Notes: 2008-12-17]]

Noisebridge - User contributions [en]

Machine Learning