Machine Learning

From Noisebridge
Jump to navigation Jump to search
The printable version is no longer supported and may have rendering errors. Please update your browser bookmarks and please use the default browser print function instead.
Noisebridge | About | Visit | 272 | Manual | Contact | Guilds | Resources | Events | Projects | 5MoF | Meetings | Donate | (Edit)
Guilds | Meta | Code | Electronics | Fabrication | Games | Sewing | Music | AI | Neuro | Philosophy | Funding | Art | Security | Ham | Brew | (Edit)
AI | Machine Learning | Botbridge | DreamTeam | ML Tools | (Edit)

AI and reinforcement learning meetup at Noisebridge Wednesdays at 8pm.

Join the Mailing List


Machine Learning groups have been perennial at Noisebridge, accumulating knowledge, projects and meeting notes since 2008.

  • Some of our info links may be outdated, so let us know if anything is wrong and edit the wiki as needed.

Past Teachers

  • Andy McMurry

Learn about Data Science and Machine Learning




Noisebridge ML Class Slides

Code and SourceForge Site

    git clone git://
  • Send an email to the list if you want to become an administrator on the site to get write access to the git repo!

Future Talks and Topics, Ideas

  • Random Forests in R
  • Restricted Boltzmann Machines (Mike S, some day)
  • Analyzing brain cells (Mike S)
  • Deep Nets w/ Stacked Autoencoders (Mike S, some day)
  • Generalized Linear Models (Mike S, Erin L? some day)
  • Graphical Models
  • Working with the Kinect
  • Computer Vision with OpenCV


Datasets and Websites

Software Tools

Generic ML Libraries

  • Weka
    • a collection of data mining tools and machine learning algorithms.
  • scikits.learn
    • Machine learning Python package
  • scikits.statsmodels
    • Statistical models to go with scipy
  • PyBrain
    • Does feedforward, recurrent, SOM, deep belief nets.
    • c-based SVM package
  • PyML
  • MDP
    • Modular framework, has lots of stuff!
  • VirtualBox Virtual Box Image with Pre-installed Libraries listed here
  • sympy Does symbolic math
  • Waffles
    • Open source C++ set of machine learning command line tools.
  • RapidMiner
  • Mobile Robotic Programming Toolkit
  • nitime
    • NeuroImaging in Python, has some good time series analysis stuff and multi-variate response fitting.
  • Pandas
    • Data analysis workflow in python
  • PyTables
    • Adds querying capabilities to HDF5 files
  • statsmodels
    • Regression, time series analysis, statistics stuff for python
  • Vowpal Wabbit
    • "Intrinsically Fast" implementation of gradient descent for large datasets
  • Shogun
    • Fast implementations of SVMs
    • High performance scalable ML Library
  • Torch
    • MATLAB-like environment for state-of-the art ML libraries written in LUA

Deep Nets

  • Theano
    • Symbolic Expressions and Transparent GPU Integration
  • Caffe
    • Convolutional Neural Networks on GPU
  • Neurolab
    • Has support for recurrent neural nets

Online ML

Graphical Models

  • BUGS
    • MCMC for Bayesian Models
  • JAGS
    • Hierarchical Bayesian Models
  • Stan
    • A graphical model compiler
  • Jayes
    • Bayesian networks in Java
  • ToPS
    • Probabilistic models of sequences
  • PyMC
    • Bayesian Models in Python

Text Stuff

Collaborative Filtering

  • PREA
    • Personalized Recommendation Algorithms Toolkit
  • SVDFeature
    • Collaborative Filtering and Ranking Toolkit

Computer Vision

  • OpenCV
    • Computer Vision Library
    • Has ML component (SVM, trees, etc)
    • Online tutorials here
    • Generic C++ ML and Computer Vision Library
  • PetaVision
    • Developing a real-time, full-scale model of the primate visual cortex.

Audio Processing

Data Visualization

  • Orange
    • Strong data visualization component
  • Gephi
    • Graph Visualization
  • ggplot
    • Nice plotting package for R
  • MayaVi2
    • 3D Scientific Data Visualization
  • Cytoscape
    • A JavaScript graph library for analysis and visualisation
    • Web-based plotting
  • D3 Ebook
    • Has a good list of HTML/CSS/Javascript data visualization tools.
  • plotly
    • Python plotting tool

Cluster Computing

  • Mahout
    • Hadoop cluster based ML package.
  • STAR: Cluster
    • Easily build your own Python computing cluster on Amazon EC2

Database Stuff

  • MADlib
    • Machine learning algorithms for in-database data
  • Manta
    • Distributed object storage

Neural Simulation


Presentations and other Materials

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 [2]
    • 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 [3]
    • Information Theory: Entropy, Mutual Information, Gaussian Channels
    • Estimation of Misclassification [4]
    • No-Free Lunch Theorem [5]
  • 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