LM101-014: How to Build a Machine that Can Do Anything (Function Approximation)

In this episode, we discuss the problem of how to build a machine that can do anything! Or more specifically, given a set of input patterns to the machine and a set of desired output patterns for those input patterns we would like to build a machine that can generate the specified output pattern for a given input pattern. This problem may be interpreted as an example of solving a supervised learning problem. Checkout the shownotes at: www.learningmachines101.com 
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