Networks: Neural Networks Ali Cole Madison Kutchey Charly Mccown Xavier henes

Definition A directed network based on the structure of connections within an organism's brain Many inputs and only a couple outputs Excitatory or inhibiting Combination allows for complex information processing tasks Artificial neural networks Handout: Image of a neuron structure (Figure 5.6 in Newman, pg 95, or similar)

Network Characteristics Nodes and Edges Value of Inputs (Puri, Chapter 1) Neuron Types (Newman, Section 2.5) Multiple Layers ("The Basics …") Machine Learning  Feed Forward and Back Propagation

Mathematical Methods Delta rule Epoch method Gradient descent—mountian climber analogy Updates weights of neurons Special case of backpropagation method Epoch method Used for training neural networks Epoch = when algorithm goes over entire data set No way to determine perfect number of epochs for any given network Special case of backpropagation 

Research questions Applications Medicine Data Science Business/Finance Estimating Breast Cancer Risks Using Neural Networks Data Science Cloud Service for Data Analysis in Medical Information Systems Using Artificial Neural Networks Business/Finance Predicting Banking Crises with Artificial Neural Networks: The Role of Nonlinearity and Heterogeneity

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