Robots And Tech: Lecture

Showing posts with label Lecture. Show all posts

Tuesday, October 21, 2014

Lecture 07 - The VC Dimension

The VC Dimension - A measure of what it takes a model to learn. Relationship to the number of parameters and degrees of freedom. Lecture 7 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunesu.itunes.apple.com/audit/CODBABB3ZC and on the course website - http://work.caltech.edu/telecourse.html

Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND).

Monday, September 22, 2014

Lecture 16 - Radial Basis Functions

Radial Basis Functions - An important learning model that connects several machine learning models and techniques. Lecture 16 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunesu.itunes.apple.com/audit/CODBABB3ZC and on the course website - http://work.caltech.edu/telecourse.html

Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND).

Monday, August 18, 2014

Lecture 02 - Is Learning Feasible?

Is Learning Feasible? - Can we generalize from a limited sample to the entire space? Relationship between in-sample and out-of-sample. Lecture 2 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunesu.itunes.apple.com/audit/CODBABB3ZC and on the course website - http://work.caltech.edu/telecourse.html

Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND).

Tuesday, July 1, 2014

Lecture: Exoskeleton Project - Natural sensors and their contributions

Lecture: Exoskeleton Project - Natural sensors and their contributions Lecture: Exoskeleton project - Natural sensors and their contributions
Dr. Marc Blanger - Dpartement de Kinanthropologie, Facult des Sciences, Universit du Qubec Montreal

Monday, June 2, 2014

Lecture 17 - Three Learning Principles

Three Learning Principles - Major pitfalls for machine learning practitioners; Occam's razor, sampling bias, and data snooping. Lecture 17 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunesu.itunes.apple.com/audit/CODBABB3ZC and on the course website - http://work.caltech.edu/telecourse.html

Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND).

Lecture 01 - The Learning Problem

This is the old version of Lecture 1. Please go to http://youtu.be/mbyG85GZ0PI for the new version.

The Learning Problem - Introduction; supervised, unsupervised, and reinforcement learning. Components of the learning problem. Lecture 1 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunesu.itunes.apple.com/audit/CODBABB3ZC and on the course website - http://work.caltech.edu/telecourse.html

Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND).

Tuesday, May 27, 2014

Lecture 18 - Epilogue

Epilogue - The map of machine learning. Brief views of Bayesian learning and aggregation methods. Lecture 18 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunesu.itunes.apple.com/audit/CODBABB3ZC and on the course website - http://work.caltech.edu/telecourse.html

Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND).

Thursday, May 22, 2014

Lecture 13 - Validation

Validation - Taking a peek out of sample. Model selection and data contamination. Cross validation. Lecture 13 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunesu.itunes.apple.com/audit/CODBABB3ZC and on the course website - http://work.caltech.edu/telecourse.html

Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND).

Wednesday, May 21, 2014

Lecture 06 - Theory of Generalization

Theory of Generalization - How an infinite model can learn from a finite sample. The most important theoretical result in machine learning. Lecture 6 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunesu.itunes.apple.com/audit/CODBABB3ZC and on the course website - http://work.caltech.edu/telecourse.html

Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND).

Monday, May 12, 2014

Lecture 01 - The Learning Problem

The Learning Problem - Introduction; supervised, unsupervised, and reinforcement learning. Components of the learning problem. Lecture 1 of 18 of Caltech's Machine Learning Course - CS 156 by Professor Yaser Abu-Mostafa. View course materials in iTunes U Course App - https://itunesu.itunes.apple.com/audit/CODBABB3ZC and on the course website - http://work.caltech.edu/telecourse.html

Produced in association with Caltech Academic Media Technologies under the Attribution-NonCommercial-NoDerivs Creative Commons License (CC BY-NC-ND).