How do you get here?

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?

Simulator:

Simple Nearest Neighbor Nearest Neighbor Applied Pattern Nearest Neighbor Nearest 3 Neighbors

Other Nearest Neighbor Nearness as pixel difference:

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

Spam Filter Is a web page "spam"?

Spam Filter Is a web page "spam"?

Spam Filter Is a web page "spam"? How do we decide the questions???

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

Learning a Decision Tree

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

Result One neuron's weights

Making it all worth it