CSI6209 Artificial Intelligence Assignment 3

Subject Code & Title :-  CSI6209 Artificial Intelligence
Assessment Type :-  Assignment 3
Related learning outcomes from the unit outline
1. Identify appropriate intelligent system solutions for a range of computational intelligence tasks.
2. Explain the concept of computational intelligence and its associated techniques and algorithms.
3. Apply computational intelligence techniques to a range of tasks.
4. Work collaboratively to develop an intelligent system.
CSI6209 Artificial Intelligence Assignment 3

Marks Allocations:
This assignment worth 40%. It is split into 3 parts; part 1 is worth 30%; part 2 is worth 10%; part 3 is ungraded.

Team Formation:
Complete assessment 3 using the same groups you formed in assessment 2.

Over all Task :-
This assessment should elaborate on the research plan specified in the assessment 2. You should choose one or more machine learning or deep learning algorithms/architecture, implement that/them and evaluate their performance.

For implementing algorithm(s) you can code using any programming language of your choice (e.g. Python, C/C++ MATLAB) or use tools like WEKA and MATLAB Toolboxes. In Python, you may use PyBrain or PyTorch libraries for machine learning/deep learning.

CSI6209 Artificial Intelligence Assignment 3

For any machine learning based object detection/recognition system you need:
a. Take input from sensor (or download already collected and publicly available data)
b. Pre-process the data
c. Read about features responsible for identification.
d. Find a method to extract those features.
e. Train your features for specific user through any machine learning technique.

However for deep learning you do not have to separately extract features.

The task is divided into three parts.

Part 1:
You need to submit a report describing your methodology and results with a Minimum of 6 and maximum 10 pages.

Part 2:
Video reflection presented by all members each describing their respective parts of the report using MS Power Point slides and recorded by Panopto with presenter’s face and ID card (student photo ID: Student ID (preferred)/Drivers License/Passport) displayed. Video should include a demonstration of the input/output data/sample, implement/code results and discussion of the project and individual’s contributions and learning from the project. No limits on the number of slides, but the maximum time is strictly 10 minutes. The
video will only be marked up to the ten-minute mark and duration in excess will not be considered.

CSI6209 Artificial Intelligence Assignment 3

Part 3:
1. A3 incorporates a peer review report (the template is available on BLACKBOARD)
2. Every student must complete a peer-review of their group
3. This report does not carry any marks on its own but it will reflect your opinion about your peer's contribution to the group work. As some of the groups raised to me the issue of non-contributing members in their group we will use the peer review report as a guide in addition to the meeting minutes distribution list and progress history sections on the report) to decide how much of the group report marks to be awarded to the group members fairly. Therefore all the students are asked to submit the report in order for their marks to be considered for the assignment (i.e. you will get zero marks if you do not submit this report).