How do you get here? https://www.youtube.com/watch?v=dk3oc1Hr62g

Pattern Recognition & Machine Learning

Patterns Humans are excellent at recognizing patterns

Patterns Even if we can't explain how we do it…

Trick 1: Nearest Neighbor Task : predict what houses are most likely to donate to an election

Nearest Neighbor Task : predict what houses are most likely to donate to an election Know some voter registrations

Nearest Neighbor Task : predict what houses are most likely to donate to an election What should we predict for the ? marks

Nearest Neighbor Task : predict what houses are most likely to donate to an election Should we consider more than one neighbor?

Other Nearest Neighbor Nearness as pixel difference:

Trick 2: Decision Trees Sequnce of choices to make a decision Do I need an umbrella?

Learning a Decision Tree Is an email important?

Machine Learning Machine Learning : Build a general algorithm to LEARN specific patterns

Learning a Decision Tree http://aispace.org/dTree/

Human Involvement Still need to determine possible questions, things to look at

Human Involvement Still need to determine possible questions, things to look at What should we look at for these???

Trick 3: Neural Networks Biologically inspired computation

Neural Networks Biologically inspired computation

Neural Networks A simple "take umbrella" network:

Neural Networks

Sunglasses Network Image recognition network:

Sunglasses Network Image recognition network:

Enhanced Neurons Signals can be any value 0-1

Enhanced Neurons Signals can be any value 0-1 Inputs can be weighted

Enhanced Neurons Signals can be any value 0-1 Inputs can be weighted Threshold function is not all or nothing Produces values 0-1

Learning Neural network learns via training Guess for lots of known examples Update weights based on success/failure No Yes Yes No No Yes

Samples https://playground.tensorflow.org

Result One neuron's weights:

Other samples https://cs.stanford.edu/people/karpathy/convnetjs/