Description

This assignment is meant to be open$-$ended and to encourage creativity. You should choose case that

you used in Assignment $2($Power BI$)$ and apply Machine Learning concepts using Python. The

examples of application are image classification, text classification, time series or temporal analysis

and recommendations of to users based on predictive analytics.

The focus should be on a particular methodology for solving a specific task either with some

combination of developing core methods from scratch or using existing Python libraries. You also need

to consider some conceptual issues, write a program to solve the task, and evaluate your program

through experiments to compare the performance of different algorithms and methods. You must

visualize your data using Python either during data exploration or result interpretation.

Your main deliverable will be a short report $($maximum $5$ pages$)$ IEEE conference format, describing

your approach and providing several figures$/$tables to explain your results and share a link to your

actual Google Colab or upload Jupyter Notebook.

Assessment criteria:

Effort

The complexity of your technical approach

The clarity of your explanations

The performance of your implementation.

A high$-$performing approach with vague explanation will receive less credit, while a careful set of

experiments that clearly present why a particular direction turned out to be poor performance may

receive more credit.