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How do you get here? https://www.youtube.com/watch?v=dk3oc1Hr62g
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Pattern Recognition & Machine Learning
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Patterns Humans are excellent at recognizing patterns
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Patterns Even if we can't explain how we do it…
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Trick 1: Nearest Neighbor
Task : predict what houses are most likely to donate to an election
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Nearest Neighbor Task : predict what houses are most likely to donate to an election Know some voter registrations
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Nearest Neighbor Task : predict what houses are most likely to donate to an election What should we predict for the ? marks
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Nearest Neighbor Task : predict what houses are most likely to donate to an election Should we consider more than one neighbor?
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Other Nearest Neighbor
Nearness as pixel difference:
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Trick 2: Decision Trees Sequnce of choices to make a decision
Do I need an umbrella?
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Learning a Decision Tree
Is an important?
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Machine Learning Machine Learning : Build a general algorithm to LEARN specific patterns
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Learning a Decision Tree
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Human Involvement Still need to determine possible questions, things to look at
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Human Involvement Still need to determine possible questions, things to look at What should we look at for these???
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Trick 3: Neural Networks
Biologically inspired computation
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Neural Networks Biologically inspired computation
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Neural Networks A simple "take umbrella" network:
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Neural Networks
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Sunglasses Network Image recognition network:
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Sunglasses Network Image recognition network:
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Enhanced Neurons Signals can be any value 0-1
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Enhanced Neurons Signals can be any value 0-1 Inputs can be weighted
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Enhanced Neurons Signals can be any value 0-1 Inputs can be weighted
Threshold function is not all or nothing Produces values 0-1
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Learning Neural network learns via training
Guess for lots of known examples Update weights based on success/failure No Yes Yes No No Yes
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Samples
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Result One neuron's weights:
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Other samples
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