Machine Learning: Difference between revisions
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=== Future Talks and Topics === | === Future Talks and Topics === | ||
* [[Neural Network Workshop]] (Mike S, 1/26/2011) | * [[Neural Network Workshop]] (Mike S, 1/26/2011) | ||
* Recurrent Neural Networks, Boltzmann Machines (Mike S, February 2011) | * Recurrent Neural Networks, Boltzmann Machines (Mike S, February 2011) | ||
* Boosting and Bagging (Thomas, unscheduled) | * Boosting and Bagging (Thomas, unscheduled) | ||
* [[CS229]] second problem set | |||
* RPy? | * RPy? | ||
Revision as of 10:22, 6 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
Machine_Learning/Datasets
Tools
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
- Unsupervised Learning
- Hidden Markov Models
- Clustering: PCA, k-Means, Expectation-Maximization
- Graphical Modeling
- Generative Models: gaussian distribution, multinomial distributions, HMMs, Naive Bayes
- Deep Belief Networks & Restricted Boltzmann Machines
- 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
- Applications
- 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 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
- LinkedIn discussion on good resources for data mining and predictive analytics
Notes from Meetings
(Although we have stopped taking meeting notes, we meet up regularly...)
Machine Learning Meetup Notes:2010-11-17 -- Condensed feedback from Kaggle boards
Machine Learning Meetup Notes: 2010-11-03 -- GLMS in R
Machine Learning Meetup Notes: 2010-10-27 -- Linear Classification with scikits.learn
Machine Learning Meetup Notes: 2010-09-15 -- Information Retrieval talk
Machine Learning Meetup Notes: 2010-08-25 -- Organizing to go through CS 229
Machine Learning Meetup Notes: 2010-08-18 -- Hidden Markov Models (HMMs)
Machine Learning Meetup Notes: 2010-07-21 -- Intro to R
Machine Learning Meetup Notes: 2010-07-14 -- Neural Networks
Machine Learning Meetup Notes: 2010-07-07 -- Kaggle HIV, Edit Distance
Machine Learning Meetup Notes: 2010-06-30 -- DNA Overview, Kaggle HIV
Machine Learning Meetup Notes: 2010-06-22 -- PIG Tutorial
Machine Learning Meetup Notes: 2010-06-16 -- MOA, Kaggle HIV
Machine Learning Meetup Notes: 2010-06-09 -- KDD Recap, JUNG/Graph Clustering
Machine Learning Meetup Notes: 2010-06-02 -- Final official meeting before KDD submission deadline
Machine Learning Meetup Notes: 2010-05-26 -- Clustering, KDD Data Reduction
Machine Learning Meetup Notes: 2010-05-23 -- Unofficial meetup to nail down KDD cup problem set
Machine Learning Meetup Notes: 2010-05-19 -- Presentation on Hadoop and MapReduce
Machine Learning Meetup Notes: 2010-05-12 -- Group workshop on KDD data set
Machine Learning Meetup Notes: 2010-05-05 -- A Brief Tour of Statistics
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