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Lab 11. Project / Case Study
Requirements
Select an algorithm and a dataset to make a presentation / case study of 10-25 slides. The combination of an algorithm and a dataset has to be unique for each student.
The structure of the presentation should be as follows:
Introduction
Describe the context of your case study. Introduce the algorithm and possible applications
Methodology
Describe the algorithm in more detail (text, pseudocode, flowcharts) and the way it can be used on a real data set.
Case Study
Describe the selected data set(s) and the implementation of the algorithm in Python. Present the results (text and visual output) and your observations.
Conclusion
Describe the outcome of the case study and applications in real world scenarios in broader terms.
Resources
Algorithms and Libraries
You can refer to the Laboratories or use any other implementation in Python.
Useful libraries for data science in Python include:
[Machine Learning]
[Data Processing]
[Visualizations]
Datasets
You can use any open dataset. Some common sources include:
[Dataset aggregators for Machine Learning projects]
[Open Data]
