PRT565 Assessment 1 Due: Week 6
Minimum 800 Lines of Coding Exercise
Type: Individual
Aim: Develop a ML based model using any of Logistic Regression, Decision Tree or Random
Forest
Development Platform: Python (using Jupyter Notebook or any other IDE of your choice)
Dataset: Use any relevant datasets from https://www.kaggle.com/datasets OR
https://archive.ics.uci.edu/ml/datasets.php
Deliverables: Coding Script (.ipynb), with your Name and ID clearly mentioned on top
Note: Your code should be thoroughly commented and execute correctly. You may also include
coding blocks that describes the data, shows relevant statistic and completes necessary data
preprocessing and cleaning.
Minimum 800 Words of Reporting (Must include an appropriate Cover Page)
Type: Individual Reporting on the above Coding exercise
Format: Font: Times New Roman, 12 Points; Line Space: 1.5; Page Alignment: Justify
Note: Your report should contain:
• Problem Description
• Dataset Description
• Choice of Algorithm
• Description of key steps such as splitting the dataset, training and testing
• Results obtained (Accuracy) and Your overall understanding
The report should be properly formatted with appropriate headings and sub-headings. The
presentation must be professional. You may include screenshots of your relevant coding
segments while explaining.
Submit in PDF format. You can install this MS Word Plug-in:
https://www.cutepdf.com/download/CuteWriter.exe — and can print the Word document out
as a PDF file.
