https://noisebridge.net/index.php?title=Machine_Learning/NBML/Calculus&feed=atom&action=historyMachine Learning/NBML/Calculus - Revision history2016-07-28T01:13:56ZRevision history for this page on the wikiMediaWiki 1.19.1https://noisebridge.net/index.php?title=Machine_Learning/NBML/Calculus&diff=15688&oldid=prevMschachter: Created page with '=== Introduction === The most relevant Calculus for machine learning involves the [http://en.wikipedia.org/wiki/Derivative Derivatives], and the multi-dimensional version of the …'2011-01-06T16:59:38Z<p>Created page with '=== Introduction === The most relevant Calculus for machine learning involves the [http://en.wikipedia.org/wiki/Derivative Derivatives], and the multi-dimensional version of the …'</p>
<p><b>New page</b></p><div>=== Introduction ===<br />
The most relevant Calculus for machine learning involves the [http://en.wikipedia.org/wiki/Derivative Derivatives], and the multi-dimensional version of the derivative, known as the [http://en.wikipedia.org/wiki/Gradient Gradient]. If you can compute gradients, you can do [http://en.wikipedia.org/wiki/Gradient_descent Gradient Descent], the most basic form of [http://en.wikipedia.org/wiki/Optimization_%28mathematics%29 Optimization].<br />
<br />
=== Resources ===<br />
*Set of [http://www.online.math.uh.edu/HoustonACT/videocalculus/index.html video lectures].</div>Mschachter