Machine Learning: Difference between revisions
Jump to navigation
Jump to search
Mschachter (talk | contribs) mNo edit summary |
Mschachter (talk | contribs) mNo edit summary |
||
| Line 24: | Line 24: | ||
*[[Machine Learning/Kaggle HIV | HIV]] | *[[Machine Learning/Kaggle HIV | HIV]] | ||
=== [[Machine_Learning/Datasets|Datasets]] === | === [[Machine_Learning/Datasets|Datasets and Websites]] === | ||
*[http://archive.ics.uci.edu/ml/ UCI Machine Learning Repository] | *[http://archive.ics.uci.edu/ml/ UCI Machine Learning Repository] | ||
*[[DataSF.org]] | *[[DataSF.org]] | ||
| Line 30: | Line 30: | ||
*[http://www.face-rec.org/databases/ Face Recognition Databases] | *[http://www.face-rec.org/databases/ Face Recognition Databases] | ||
*[http://robjhyndman.com/TSDL/ Time Series Data Library] | *[http://robjhyndman.com/TSDL/ Time Series Data Library] | ||
*[http://getthedata.org/ Data Q&A Forum] | |||
*[http://metaoptimize.com/qa/ Metaoptimize] | |||
*[http://www.quora.com/Machine-Learning Quora ML Page] | |||
=== [[Machine Learning/Tools | Software Tools]] === | === [[Machine Learning/Tools | Software Tools]] === | ||
Revision as of 21:20, 15 June 2011
Next Meeting
- When: Wednesday, 6/15/2011 @ 7:30-9:00pm
- Where: 2169 Mission St. (back corner classroom)
- Topic: Undeclared
- Details:
- Presenters: ???
Future Talks and Topics
- Support Vector Machines in R (6/22/2011)
- Boltzmann Machines, Deep Nets (Mike S, August 2011)
- Graphical Models (Tony)
Mailing List
https://www.noisebridge.net/mailman/listinfo/ml
Projects
- Small Group Subproblems
- Fundraising
- Noisebridge Machine Learning Course
- Kaggle Social Network Contest
- KDD Competition 2010
- HIV
Datasets and Websites
- UCI Machine Learning Repository
- DataSF.org
- Infochimps
- Face Recognition Databases
- Time Series Data Library
- Data Q&A Forum
- Metaoptimize
- Quora ML Page
Software Tools
- OpenCV
- Computer Vision Library
- Has ML component (SVM, trees, etc)
- Online tutorials here
- Mahout
- Hadoop cluster based ML package.
- Weka
- a collection of data mining tools and machine learning algorithms.
- MOA (Massive Online Analysis)
- Offshoot of weka, has all online-algorithms
- scikits.learn
- Machine learning Python package
- LIBSVM
- c-based SVM package
- PyML
- MDP
- Does not stand for Markov Decision Process :(
- Orange
- Strong data visualization component
- Journal of Machine Learning Software List
- VirtualBox Virtual Box Image with Pre-installed Libraries listed here
- Theano: Symbolic Expressions and Transparent GPU Integration
- Waffles
- Open source C++ set of machine learning command line tools.
- RapidMiner
- Mobile Robotic Programming Toolkit
- Gephi
- Graph Visualization
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
- Face Recognition Algorithms
Topics to Learn and Teach
NBML Course - Noisebridge Machine Learning Curriculum (work-in-progress)
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