Assessment 2 Information

Your Task

Evaluate the Neural Network based predictive modelling capability in the Orange Data Mining Application.

The report 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.

Assessment Instructions

You have been introduced to the Orange Data Mining application in class. Please ensure you have  downloaded it and are familiar with its operation. You will also be provided with a dataset containing

images. Well-reasoned use of Generative AI is encouraged. However, generic and irrelevant  content will be heavily penalised in the marking.

•    Image Classification

a.  Construct a predictive model using the Image Analytics widgets in Orange. b.  Create a test data set if it does not exist.

c.  Classify the images using your model.

•    Re- analyse dataset used in Assessment 1

a.  Construct a predictive model using the Neural Network widget in Orange. b.  Classify the outcomes using your model.

•    Evaluate the effectiveness in both cases in terms of

a.  Accuracy

b.  Utility

c.  Method used

d.  ease of use

•    Recommend improvements or suggest other applications.

•   Summarise your findings.

•    Include a list of references that is directly related to the content. Each reference needs to be linked to at least one specific point in the content of your assessment. It is expected

that you will have at least 3 relevant references.

•    Upload the file that contains your prediction model in Orange to the dropbox provided on the assessment page.

•    Investigate the use of Generative AI (eg: chatGPT) to enhance your analysis. Clearly state the prompts and steps undertaken.

•   Submit report in Turnitin.

Important Study Information

Academic Integrity Policy

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.

What is academic integrity and misconduct?

What are the penalties for academic misconduct?

What are the late penalties?

How can I appeal my grade?

Click here for answers to these questions:

http://www.kbs.edu.au/current-students/student-policies/.

Word Limits for Written Assessments

Submissions that exceed the word limit by more than 10% will cease to be marked from the point at which that limit is exceeded.

Study Assistance

Students may seek study assistance from their local Academic Learning Advisor or refer to the resources on the MyKBS Academic Success Centre page. Click herefor this information.