Topic 8 - Regression and Neural Networks

This week, the lecture is about regression and neural networks.Regression models is about using mathematical equation to relate one or more numeric input attributes to a single numeric output attribute. We can use regression models for fit data, time-series data (for forecast) or other data (for prediction). Some of the terms use are R2(squared) and t intercept.

Neural networks is computer technology that attempts to build computers that will operate like a human brain. The machines possess simultaneous memory storage and works with ambiguous information. Neural networks accept inputs and outputs that are numerical, and where the relationships between inputs and outputs are not linear or the input data are not normally distributed.Some applications include approval of loan applications, fraud prevention and time-series forecasting.