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BUSI 651 – Machine Learning
Assignment 2:

The provided dataset “Franchises Dataset” contains data collected from different 100 franchises.
The data contains the net profit (million $) for each franchise, the counter sales (million $), the
drive-through sales (million $), and the type of the franchise.

Address the following questions:

a) Develop a Neural Network (NN) prediction model for the net profit (Number of layers =
3, dense layers, activation function of Tan, number of nodes in each layer = 20).
b) What is the forecast of the net profit, if the counter sales are 500,000 $, drive-through
sales are 700,000$, and the franchise is a pizza store. Comment on the forecasted value.
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.

Due to June 8, 2022.
Franchise_data
Net Profit Counter Sales Drive-through Sales Business Type
2 8.4 7.7 1 Café 1
1.3 3.3 4.5 1 Pizza Store 2
1.2 5.8 8.4 2 Burger store 3
2.4 10 7.8 3
0.7 4.7 2.4 1
1.3 7.7 4.8 1
1.1 4.5 2.5 1
2.3 8.6 3.4 3
0.9 5.9 2 1
1.6 6.3 4.1 3
2 8.4 7.7 1
1.3 3.3 4.5 1
1.7 5.8 8.4 1
1.4 10 7.8 2
1.2 4.7 2.4 3
1.8 7.7 4.8 3
1.6 4.5 2.5 3
1.8 8.6 3.4 1
1.4 5.9 2 3
1.1 6.3 4.1 1
1.5 8.4 7.7 2
1.3 3.3 4.5 1
1.2 5.8 8.4 2
2.4 10 7.8 3
1.2 4.7 2.4 3
1.3 7.7 4.8 1
1.1 4.5 2.5 1
1.3 8.6 3.4 2
0.9 5.9 2 1
1.6 6.3 4.1 3
2 8.4 7.7 1
0.8 3.3 4.5 2
2.2 5.8 8.4 3
2.4 10 7.8 3
1.2 4.7 2.4 3
0.8 7.7 4.8 2
1.6 4.5 2.5 3
1.8 8.6 3.4 1
0.9 5.9 2 1
1.6 6.3 4.1 3
2 8.4 7.7 1
0.8 3.3 4.5 2
1.2 5.8 8.4 2
1.9 10 7.8 1
0.7 4.7 2.4 1
0.8 7.7 4.8 2
0.6 4.5 2.5 2
2.3 8.6 3.4 3
0.9 5.9 2 1
1.6 6.3 4.1 3
2 8.4 7.7 1
1.3 3.3 4.5 1
1.2 5.8 8.4 2
2.4 10 7.8 3
0.7 4.7 2.4 1
1.8 7.7 4.8 3
0.6 4.5 2.5 2
2.3 8.6 3.4 3
0.4 5.9 2 2
1.1 6.3 4.1 1
2.5 8.4 7.7 3
1.8 3.3 4.5 3
2.2 5.8 8.4 3
2.4 10 7.8 3
1.2 4.7 2.4 3
0.8 7.7 4.8 2
1.1 4.5 2.5 1
1.3 8.6 3.4 2
0.9 5.9 2 1
0.6 6.3 4.1 2
2.5 8.4 7.7 3
1.3 3.3 4.5 1
2.2 5.8 8.4 3
1.9 10 7.8 1
0.2 4.7 2.4 2
1.8 7.7 4.8 3
1.6 4.5 2.5 3
2.3 8.6 3.4 3
1.4 5.9 2 3
0.6 6.3 4.1 2
1.7 8.4 7.7 2
1.8 3.3 4.5 3
2.6 5.8 8.4 3
1.4 10 7.8 2
0.2 4.7 2.4 2
1 7.7 4.8 2
0.6 4.5 2.5 2
2.3 8.6 3.4 3
1.6 5.9 2 1
0.6 6.3 4.1 2
2.5 8.4 7.7 3
1.6 3.3 4.5 3
1.2 5.8 8.3 2
1.9 9.8 7.8 1
1.2 4.7 2.4 3
1.8 7.7 4.8 3
0.6 4.5 2.5 2
1.3 9.1 3.4 2
1 5.9 2.2 1
1.8 6.3 4.2 3

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