About
Machine learning is a field focused on making machines learn to make predictions from examples. It combines elements of mathematics, computer science, and statistics with applications in biology, physics, engineering and any other area where automated prediction is necessary. This short summer school is an intense introduction to the basics of machine learning and learning theory with various additional advanced topics covered. It is appropriate for anyone interested in learning this material.
Videos
Introduction

Welcome
Apr 19, 2007
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4126 views

Welcome to Chicago, and a (brief!) introduction to machine learning
Feb 25, 2007
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5880 views
Lectures

Diffusion Maps, Spectral Clustering and Reaction Coordinates of Dynamical System...
Feb 25, 2007
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10920 views

Empirical Comparisons of Learning Methods & Case Studies
Feb 25, 2007
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6174 views

Game Dynamics with Learning and Evolution of Universal Grammar
Feb 25, 2007
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3295 views

Online Learning with Kernels
Feb 25, 2007
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7114 views

Categorical Perception + Linear Learning = Shared Culture
Feb 25, 2007
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3541 views

The Dynamics of AdaBoost
Feb 25, 2007
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24744 views

Learning on Structured Data
Feb 25, 2007
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11791 views

On the Borders of Statistics and Computer Science
Feb 25, 2007
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14044 views

Some Aspects of Learning Rates for SVMs
Feb 25, 2007
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5768 views

Semi-supervised Learning, Manifold Methods
Feb 25, 2007
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16475 views

Evidence Integration in Bioinformatics
Feb 25, 2007
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5142 views
Bayesian Learning
Feb 25, 2007
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41428 views

Adventures with Camille
Feb 25, 2007
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4356 views

Learning variable covariances via gradients
Feb 25, 2007
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3754 views
Energy-based models & Learning for Invariant Image Recognition
Feb 25, 2007
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13319 views

Fingerprints of Rhthm in Natural Language
Feb 25, 2007
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3504 views

Algorithms for Learning and their Estimates
Feb 25, 2007
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3801 views

Feasible Language Learning
Feb 25, 2007
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3545 views

An introduction to grammars and parsing
Feb 25, 2007
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10499 views
Tutorial on Machine Learning Reductions
Feb 25, 2007
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16463 views
Online Learning and Game Theory
Feb 25, 2007
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28927 views

Introduction to Kernel Methods
Feb 25, 2007
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14760 views

Learning on Structured Data
Feb 25, 2007
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3978 views

On Optimal Estimators in Learning Theory
Feb 25, 2007
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3652 views

Learning patterns in omic data: applications of learning theory
Feb 25, 2007
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4472 views

On the evolution of languages
Feb 25, 2007
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3710 views

Learning to Signal
Feb 25, 2007
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3957 views
Multiscale analysis on graphs
Feb 25, 2007
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4625 views

Trees for Regression and Classification
Feb 25, 2007
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10461 views

Information Geometry
Feb 25, 2007
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35585 views

Generalization bounds
Feb 25, 2007
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8689 views

Semi-supervised Learning, Manifold Methods
Feb 25, 2007
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9198 views

Introduction to Kernel Methods
Feb 25, 2007
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17920 views
Interviews with students

Short interviews MLSS05 Chicago by John Langford
Feb 25, 2007
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6513 views
Debates

Lunch debate 23.5.2005
Feb 25, 2007
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6880 views

Lunch debate 25.5.2005
Feb 25, 2007
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5481 views

Lunch debate 27.5.2005
Feb 25, 2007
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3679 views

Lunch debate 24.5.2005
Feb 25, 2007
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5196 views