Demonstrate proficiency in the following areas:

LO 9.9.3 Architecture of Neural Networks (NNs)

For example:

A. Explain the role of the transformation rule.

B. Explain the relationship between the deep predictor and transformation rules.

C. Explain the properties of Sigmoid, Hyperbolic tangent (tanh), and Rectifier

linear unit (ReLU) functions.

D. Describe how a NN can serve as a linear regression tool.

E. Describe the feedforward operation and its relationship to backpropagation.

Reading 9.9: Aldridge, I. and M. Avellaneda. (2019). Neural Networks in Finance: Design and Performance. The Journal of Financial Data Science, 1(4), 39-62.

Article  URL: https://fdpinstitute.org/Big-Data-and-Machine-Learning-in-the-Financial-Industry/