DATA4800 Artificial Intelligence and Machine Learning

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Assessment 2 Information

Subject Code:

DATA4800

Subject Name:

Artificial Intelligence and Machine Learning

Assessment Title:

Individual Evaluation Activity (Evaluating Neural Network Models)

Assessment Type:

Individual Implementation and Problem Solving (Puzzle)

Word Count:                   1000             Words                                (+/- 10%)

Weighting:

30 %

Total Marks:

30

Submission:

Turnitin

Due Date:

In-class, Week 10

Your Task

Evaluate the predictive modelling capability of neural networks and other prediction models in the Orange Data Mining Application. The assessment will involve implementing predictive models using software and solving various machine learning problems encountered in business. The assessment is worth 30 marks  (see rubric for allocation of these marks).

Assessment Description

There has been a recent advent of Neural Networks including applications in deep learning.

Analytics professionals can run basic Deep Learning applications via the browser and no-code platforms as the algorithms use hardware accessed via the cloud to provide the required performance.

In this assessment, you will implement an image classification model using Orange Data Mining’s image analytics toolbox. You will be provided with a dataset containing images.

Assessment Instructions

In class: Implementation. Use the Orange data mining software to perform both deep learning- based image classification and classical predictive analytics tasks.

.    Image Classification —Construct a predictive model using the Image Analytics widgets in

Orange.

.    Analyse tabular data using Neural Networks (NN)— Construct a predictive model using NN and other widgets in Orange.

In class: Problem Solving (Puzzle). Based on the Orange output, solve the accompanying puzzles in the assessment sheet designed to test your understanding of various prediction models and general knowledge on machine learning.

Deliverables: By the end of the workshop, you must submit your:

.    Orange workflow file (.ows), via the file submission dropbox

.    Your answer sheet containing answers to the puzzle.

No marks will be awarded for the assessment unless both the Orange workflow and the answer sheet have been submitted correctly as specified above. No marks will be awarded to students who  share/accept workflows or puzzle answers with/from others. 

Important Study Information

Academic Integrity and Conduct Policy

https://www.kbs.edu.au/admissions/forms-and-policies

KBS values academic integrity. All students must understand the meaning and consequences of cheating, plagiarism and other academic offences under the Academic Integrity and Conduct Policy.

Please read the policy to learn the answers to these questions:

·    What is academic integrity and misconduct?

·    What are the penalties for academic misconduct?

·     How can I appeal my grade?

Late submission of assignments (within the Assessment Policy)

https://www.kbs.edu.au/admissions/forms-and-policies

Length Limits for Assessments

Penalties may be applied for assessment submissions that exceed prescribed limits.

Study Assistance

Students may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centrepage. Further details can be accessed at

https://elearning.kbs.edu.au/course/view.php?id=1481

Generative AI Traffic Lights

Please see the level of Generative AI that this assessment has been designed to accept:

 

Traffic Light

Amount of Generative

Artificial Intelligence (AI)

usage

 

Evidence Required

 

This assessment (✓)

 

 

 

 

 

 

 

Level 1

This assessment fully

integrates Generative AI, encouraging you to

harness the

technology's full

potential in collaboration with your own expertise.

It will highlight your ability to demonstrate how

effectively you can work  alongside AI to achieve   sophisticated outcomes, blending human intellect and artificial intelligence.

Your collaboration with AI

must be clearly referenced and documented in the

appendix of your submission, including all prompts and

responses used for the

assessment.

 

 

 

 

 

 

 

 

Level 2

This assessment invites

you to engage with

Generative AI as a

means of expanding

your creativity and idea generation.

It will highlight your ability

to complement your

original thinking with the capabilities of AI. For

example, through

brainstorming and

preliminary concept

development.

Your collaboration with AI

must be clearly referenced and documented in the

appendix of your submission, including all prompts and

responses used for the

assessment.

 

 

 

 

 

 

 

✓

 

 

 

 

 

 

Level 3

This assessment

showcases your

individual knowledge

and skills in the absence

of Generative AI

support.

It will highlight your

personal abilities. For

example, to analyse,

synthesise, and create based on your own

understanding and

learning.

Use of generative AI is

prohibited and may

potentially result in penalties for academic misconduct,

including but not limited to a

mark of zero for the

assessment.

 

Assessment Marking Guide

Standards for this Task

Points

Feedback

Implementation and Problem Solving

口   Correctly implemented a prediction model to classify images as specified in the accompanying sheet.

口   Correctly solved puzzles in the accompanying assessment sheet.

For a higher-grade students need to:

•     Provide a justified interpretation of the model outcome.

 

 

 

 

 

 

/25

 

Class Participation

 

•    Actively participated in discussions during class and volunteered to ask and answer questions (weeks 6–9). The level of participation    will influence the grade.

 

 

 

/5

 

 

/30

 

 


2024-04-05