FINS3648/FINS5548 Python Assignment

FinTech Use Case
Compare and contrast results from TWO models designed to predict levels of potential sale price
(fair value) of real estate assets in a specific area given predefined asset and environmental
characteristics (modified data is provided).
Specifically, your IoT FinTech team members are interested to see the effect of “number of
rooms” variable on the mean asset value. 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 critically explain
your steps and results and show model coefficients and model accuracy, for example in mean
square error (MSE) and/or 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 with ‘’’’’’ 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.
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