KL Divergence

Linear Digressions

• Episode: KL Divergence
• Website: Linear Digressions
• Feed URL: http://feeds.feedburner.com/udacity-linear-digressions?format=xml
• Duration: 00:25:38
• Published: 2017-08-07 05:07

Kullback Leibler divergence, or KL divergence, is a measure of information loss when you try to approximate one distribution with another distribution.  It comes to us originally from information theory, but today underpins other, more machine-learning-focused algorithms like t-SNE.  And boy oh boy can it be tough to explain.  But we're trying our hardest in this episode!