Recommendation-System-and-Market-Basket-Analysis

CCT College Dublin Continuous Assessment | Assignment Title: Integrated CA Data Visualization Techniques and Machine Learning

Assessment details Questions:

1. Discuss and explain the purpose of a recommendation system for online retail business in machine learning. Briefly compare Content and Collaborative filtering using any dataset of your choice (Datasets used in the class tutorials or exercises are not allowed to use in this CA2). Train and test machine learning models for the user-user or item-item collaborative filtering. Justify your recommendations for the considered scenario by providing a conceptual insight.
2. Perform Market Basket Analysis on the chosen dataset by using Apriori and FP growth algorithms. Can you express major divergence between these models? Compare and contrast the machine learning results obtained based on both algorithms. (50, 50 = 100 marks)
3. Create an interactive Dashboard aimed at older adults (65+) with specific features to summarise the most important aspects of the data and identify through your visualisation why this dataset is suitable for Machine Learning models in an online retail business. Explain how your dashboard is designed with this demographic in mind. (100 marks) Submission Requirements All assessment submissions must meet the minimum requirements listed below. Failure to do so may have implications for the mark awarded. All assessment submissions must: ● Include the CCT assessment cover page. ● The code and datasets should be provided and uploaded in zip format on Moodle. ● Use any version control system (for example Github) to show the weekly progress of your CA2 and there should be at least 5 commits. You should provide access to the Github repository to your lecturers. ● Maximum Number of Words for the report (2000 +- 10% words excluding title page, diagrams, code and HARVARD References). ● Must be clearly specified the number of words used in the report. ● Describe the contribution of each team member in the project clearly and use a bar chart or pie chart to represent the effort and time spent during this project. ● The rubric is provided for the detailed breakdown of marks at the end of this CA. ● Use Harvard Referencing when citing third party material ● Make sure the dataset should not be used in any previous assessments/ lectures/ tutorials for this CA. ● Be the student’s own work. ● Any dataset used in the class is not allowed to use in CA