LM101-015: How to Build a Machine that Can Learn Anything (The Perceptron)

In this 15th episode of Learning Machines 101, we discuss the problem of how to build a machine that can learn any given pattern of inputs and generate any desired pattern of outputs when it is possible to do so! It is assumed that the input patterns consists of zeros and ones indicating possibly the presence or absence of a feature. Check out: www.learningmachines101.com to obtain transcripts of this podcast!!!

Episode metadata supplied by the publisher feed · Published Oct 27, 2014

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LM101-015: How to Build a Machine that Can Learn Anything (The Perceptron)

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This episode was published on October 27, 2014.

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