CIT3C15 Machine Learning For Developers

Project Specification

With the proposed problem statement and chosen dataset, you are required to build a machine learning model and deploy it as a web application using Flask.

Your Project Report should include, but not limited to, the following sections:

a) Cover Page – to include your name and matriculation number
b) Introduction – description of the topic that you propose to work on and the problem statement

c) Data Exploration, Data Preparation and Feature Selection
d) Methods and Improvements- analysis of various algorithms that you use to train the model, and the ways you apply to improve the model (e.g. parameter tuning, feature engineering, different feature combination etc.)
e) Results and Analysis
f) Conclusion
g) References - List of resources you have used as research materials to help you in the development.

 

Demonstration/ Presentation

You are to do a 10 min demonstration/presentation of your project. You must be prepared to show and explain your codes when requested during the presentation.

Project Source Codes

Submit the entire project folder as a zipped file into the LMS under the Assessment section. Your zipped file should include the following:
• PowerPoint Slides
• Dataset (2) : Original Dataset and Dataset after feature engineering
• Juypter notebook file (*.ipynb)
• Flask web application files (*.ipynb, *.html)

Please ensure that you have a backup copy of your project in case there is a problem with the online submission.