question archive BUSI 651 – Machine Learning Assignment 2: A Realtor in Massachusetts is analyzing the relationship between the sale price of a home (in $), it's the square footage (in ft2), the number of bedrooms, the number of bathrooms, and a colonial dummy variable (colonial equals 1 if a colonial-style home; 0 otherwise)
BUSI 651 – Machine Learning Assignment 2: A Realtor in Massachusetts is analyzing the relationship between the sale price of a home (in $), it's the square footage (in ft2), the number of bedrooms, the number of bathrooms, and a colonial dummy variable (colonial equals 1 if a colonial-style home; 0 otherwise)
Subject:Computer SciencePrice: Bought3
BUSI 651 – Machine Learning
Assignment 2:
A Realtor in Massachusetts is analyzing the relationship between the sale price of a home (in $), it's the square footage (in ft2), the number of bedrooms, the number of bathrooms, and a colonial dummy variable (colonial equals 1 if a colonial-style home; 0 otherwise). The relater collects data of 36 sales in Massachusetts for the analysis. The attached file “Assignment – Dataset 2” contains the data.
Address the following questions:
a) Develop a Neural Network (NN) prediction model for the sales price (Number of layers = 3, dense layers, activation function of “Relu”, number of nodes in each layer = 32).
b) Predict the price of 2100 ft2 colonial style home with two bedrooms and two bathrooms.
c) What are the limitations of the model?
Submit a PDF file for your answers as well as the excel sheet. Include the Python code in the PDF.
