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).
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.
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.
- Construct a predictive model using the Image Analytics widgets in Orange.
- Create a test data set if it does not exist.
- Classify the images using your model.
- Re- analyse dataset used in Assessment 1
- Construct a predictive model using the Neural Network widget in Orange.
- Classify the outcomes using your model.
- Evaluate the effectiveness in both cases in terms of
- Method used
- 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.
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