Machine Learning: Difference between revisions
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*Estimation of Misclassification [http://www.cedar.buffalo.edu/~srihari/CSE555/Chap9.Part5.pdf] | *Estimation of Misclassification [http://www.cedar.buffalo.edu/~srihari/CSE555/Chap9.Part5.pdf] | ||
*Classifier Combination [http://www.cedar.buffalo.edu/~srihari/CSE555/Chap9.Part6.pdf] | *Classifier Combination [http://www.cedar.buffalo.edu/~srihari/CSE555/Chap9.Part6.pdf] | ||
=== Possible Projects === | === Possible Projects === | ||
*[[Online Machine Learning Toolkit]] | *[[Online Machine Learning Toolkit]] | ||
=== Presentations and other Materials === | === Presentations and other Materials === | ||
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* [[Awesome Machine Learning Applications]] -- A list of cool applications of ML | * [[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. | * [[Hands-on Machine Learning]], a presentation [[User:jbm|jbm]] gave on 2009-01-07. | ||
=== Notes from Meetings === | === Notes from Meetings === |
Revision as of 09:58, 15 April 2010
Come to the ML-Meetup @ Noisebridge
Meetings are at at 2169 Mission St. We're currently voting on when to have the next weekly meeting:
http://doodle.com/9w2x7vf3xvsz4k5h
Topics to Learn and Teach
- Linear Regression (Mike S volunteered to teach)
- Linear Discriminants
- Decision Theory (Bayesian)
- Maximum Likelihood
- Neural Nets/Radial Basis Functions
- Bias/Variance Tradeoff, VC Dimension
- Clustering/PCA
- No-Free Lunch Theorem [1]
- Graphical Modeling
- Support Vector Machines
- k-Means Clustering
- Reinforcement Learning
- Bagging, Bootstrap, Jacknife [2]
- Generative Models: gaussian distribution, multinomial distributions, HMMs, Naive Bayes
- Metric spaces and what they mean
- Fundamentals of probabilities
- Information Theory: Entroy, Mutual Information, Gaussian Channels
- A basic decision tree builder, recursive and using entropy metrics
- Estimation of Misclassification [3]
- Classifier Combination [4]
Possible Projects
Presentations and other Materials
- Awesome Machine Learning Applications -- A list of cool applications of ML
- Hands-on Machine Learning, a presentation jbm gave on 2009-01-07.
Notes from Meetings
Machine Learning Meetup Notes: 2010-04-14 -- (re)Starting new Machine Learning Meetup!
(We've fallen off the notes bandwagon, sorry.)
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