CS 81 Section 2
Week 1 Summary
1/19/12:
Thomas Shultz
A neural network primer
Computational Developmental Psychology, Chapters 1 and 2 (1995)
Neural Networks:
Neural networks are function-approximating models consisting of many highly connected simple units, each one representing a single neuron.
Composed of discrete units loosely modeling neurons, each unit has:
NNets can learn non-linear functions if activation function is non-linear
Use Back-Propagation to train networks
Networks can have any topology–time sensitive variants exist
Possible to overtrain for inputs–networks will learn the easiest feature to classify first
Psychological Development: