Reference no: EM132414182

FINS3648/FINS5548 Banking, Finance and Technology - Python Assignment, University of New South Wales, Australia

FinTech Use Case -

Compare and contrast results from TWO models designed to predict levels of short-term rental income of real estate assets in a specific area given predefined asset and environmental characteristics (modified data is provided).

Specifically, your FinTech team members are interested to see the effect of "number of rooms" variable on the mean short-term rental price derived from the asset. You are free to choose any two relevant models (we have covered few ML variations starting from a base simple OLS). Your task is to explain your steps and results and show model coefficients and model accuracy, for example in mean square error (MSE) and R^2.

Model choices

1. Linear Regression

2. RANSAC Regressor

3. LASSO

4. Polynomials

5. Decision Tree

6. Random Forest

Your team members are keen to learn about python and would like to see and read the python script with simple explanations of your steps. As a result, delivery is in one python.py script format as <studendtID_Name.py> with '''<text>''' explanations of your steps. The aim is to describe your detailed steps from input variables to model parameters and compare and contrast final results in a critical, concise and logical way.

Attachment:- Banking, Finance and Technology - Python Assignment Files.rar