Machine Learning: Difference between revisions

From Noisebridge
Jump to navigation Jump to search
mNo edit summary
Line 34: Line 34:
* [[Machine Learning/moa]]
* [[Machine Learning/moa]]
* [[Machine Learning/SVM]]
* [[Machine Learning/SVM]]
=== 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]
* [[Media:Brief_statistics_slides.pdf]], a presentation given on statistics for the machine learning group
* [http://www.linkedin.com/groupAnswers?viewQuestionAndAnswers=&discussionID=20096092&gid=77616&trk=EML_anet_qa_ttle-0Nt79xs2RVr6JBpnsJt7dBpSBA LinkedIn] discussion on good resources for data mining and predictive analytics
* [http://www.face-rec.org/algorithms/ Face Recognition Algorithms]


=== Topics to Learn and Teach ===
=== Topics to Learn and Teach ===
Line 73: Line 81:
*Applications
*Applications
** Collective Intelligence & Recommendation Engines
** Collective Intelligence & Recommendation Engines
=== 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]
* [[Media:Brief_statistics_slides.pdf]], a presentation given on statistics for the machine learning group
* [http://www.linkedin.com/groupAnswers?viewQuestionAndAnswers=&discussionID=20096092&gid=77616&trk=EML_anet_qa_ttle-0Nt79xs2RVr6JBpnsJt7dBpSBA LinkedIn] discussion on good resources for data mining and predictive analytics
* [http://www.face-rec.org/algorithms/ Face Recognition Algorithms]


=== [[Machine Learning/Meeting Notes|Meeting Notes]]===
=== [[Machine Learning/Meeting Notes|Meeting Notes]]===

Revision as of 01:01, 9 January 2011

Next Meeting

  • When: Wednesday, 1/12/2010 @ 7:30-9:00pm
  • Where: 2169 Mission St. (back corner classroom)
  • Topic: Semi-supervised Learning
  • Details:
  • Presenter: Clay W

Future Talks and Topics

  • Neural Network Workshop (Mike S, 1/26/2011)
  • Recurrent Neural Networks, Boltzmann Machines (Mike S, February 2011)
  • Boosting and Bagging (Thomas, unscheduled)
  • CS229 second problem set
  • RPy?

Mailing List

https://www.noisebridge.net/mailman/listinfo/ml

Projects

Datasets

Software Tools

Presentations and other Materials

Topics to Learn and Teach

CS229 - The Stanford Machine learning Course @ noisebridge

  • Supervised Learning
    • Linear Regression
    • Linear Discriminants
    • Neural Nets/Radial Basis Functions
    • Support Vector Machines
    • Classifier Combination [1]
    • A basic decision tree builder, recursive and using entropy metrics
  • 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 [2]
    • Information Theory: Entropy, Mutual Information, Gaussian Channels
    • Estimation of Misclassification [3]
    • No-Free Lunch Theorem [4]
  • Machine Learning SDK's
    • OpenCV ML component (SVM, trees, etc)
    • Mahout a Hadoop cluster based ML package.
    • Weka a collection of data mining tools and machine learning algorithms.
  • Applications
    • Collective Intelligence & Recommendation Engines

Meeting Notes

Retrieved from "https://wiki.extremist.software/index.php?title=Machine_Learning&oldid=15742"