Difference between revisions of "10-601 Neural networks and Deep Belief Networks"
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− | This a lecture used in the [[Syllabus for Machine Learning 10- | + | This a lecture used in the [[Syllabus for Machine Learning 10-601B in Spring 2016]] |
=== Slides === | === Slides === | ||
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=== Readings === | === Readings === | ||
− | * Mitchell: Ch. 4, | + | * Mitchell: Ch. 4, Murphy Ch 16.5 |
=== What You Should Know Afterward === | === What You Should Know Afterward === | ||
− | + | * What functions can be expressed with multi-layer networks that a single layer cannot express | |
− | * What can be | + | * The backpropagation algorithm, and what loss is associated with it |
− | * | + | * In outline, how deep neural networks are trained |
− | * | ||
− |
Latest revision as of 16:44, 6 January 2016
This a lecture used in the Syllabus for Machine Learning 10-601B in Spring 2016
Slides
- William's slides: in Powerpoint, in PDF
Readings
- Mitchell: Ch. 4, Murphy Ch 16.5
What You Should Know Afterward
- What functions can be expressed with multi-layer networks that a single layer cannot express
- The backpropagation algorithm, and what loss is associated with it
- In outline, how deep neural networks are trained