In this episode of Learning Machines 101, we review Chapter 6 of my book “Statistical Machine Learning” which introduces methods for analyzing the behavior of machine inference algorithms and machine learning algorithms as dynamical systems. We show that when dynamical systems can be viewed as special types of optimization algorithms, the behavior of those systems even when they are highly nonlinear and high-dimensional can be analyzed. Learn more by visiting: www.learningmachines101.com and www.statisticalmachinelearning.com .
LM101-006: How to Interpret Turing Test Results
LM101-005: How to Decide if a Machine is Artificially Intelligent (The Turing Test)
LM101-004: Can computers think? A mathematician.s response
LM101-003: How to Represent Knowledge using Logical Rules
LM101-002: How to Build a Machine that Learns to Play Checkers
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