Python in Real Estate Valuations – ML Algorithms – Engineering Assignment Help

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Assingment Task :

The purpose of this Use Case / Story is

(1) to demonstrate number of ML algorithms as used in an experimental setting and

(2) to demonstrate innovation in FinTech and Real Estate Financing and Valuations

(3) to expand on previous discussions related to Regression Analysis.

(4) to showcase the reasons for using ML algorithms 

 

Problem

As a start we need to understand the use case. We have requirement to predict value of real estate asset given certain parameters collected from other external sources. Then we need to find a method that is robust and tested to be able to confidently deliver on the solution. We start to analyze all available data sources. In this case we operate with already cleaned and preprocessed data as per below Attributes:

For this we choose standard ML database – Boston Housing Data.

CRIM per capita crime rate by town

ZN proportion of residential land zoned for lots over 25,000 sq.ft.

INDUS proportion of non-retail business acres per town

CHAS Charles River dummy variable (= 1 if tract bounds river; 0 otherwise)

NOX nitric oxides concentration (parts per 10 million)RM average number of rooms per dwelling

AGE proportion of owner-occupied units built prior to 1940

DIS weighted distances to five Boston employment centres

RAD index of accessibility to radial highway

 

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