Machine Learning & Pattern Recognition

CMPS 530

Machine Learning & Pattern Recognition

Thursday 6-9 pm

PROJECT 1 Due: December 4, 2020

Team: Names:______________________________________________________________

Notes:

Project Total (100 points)

Python Code: make sure the python code is running, provide screenshots and/or actual python script

with the project document

**This is a team project but each one should upload on the teams separately and also email me at

[email protected] the project pdf document.

Read the white paper on Intelligent Supply Chain (in the class materials folder)

The Groceries Market Basket Dataset, which can be found in the class materials folder with file name:

groceries.xlsx will be used for Project 1. The dataset contains 9835 transactions by customers shopping

for groceries. The data contains 169 unique items.

Your tasks:

1) Form a team of 3 members (at most)

2) Read the white paper and theorize what the new paradigm of supply chain is. Write a 1000

words minimum (5000 words maximum) position paper outlining how new techniques can be

used to improve product supply chains

3) Use the groceries data set and perform EDA (use python or weka)

4) Program/Develop a new technique (bonus points) (hybrid)/Use existing Machine learning

techniques to answer the below statement:

The three items most often purchased together are: (ok to solve using EDA)

Predict whether dairy products and vegetables are most often purchased together, could have a binary

outcome: OR

Predict whether vegetables and meat products are most often purchased together, could have a binary

outcome:

5) Use Cross validation to make sure your model and technique predicts correctly