Notes to: Machine Learning 101 Episode 10

This podcast series is an excellent overview of machine learning.

  • Nature vs Nurture
  • Deterministic vs probabilistic view of reality
  • environments are not intrinsically probabilistic or non probabilistic
  • goal is to determine probability weights of events
  • Bayesian priors (dog genetic wiring example)
  • Maximum likelihood estimation probabilistic law that makes observed data most likely
  • Math estimation problem
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