Lab 11. Project / Case Study
This week is for working on the laboratory project and preparing the final presentation.
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 list of algorithms can be found on MS Teams / Laboratory channel
- If you choose an algorithm that was used in the Laboratory, you will have to use another dataset.
- If you choose another algorithm, you can also use a dataset from the Laboratory.
The structure of the presentation should be as follows:
Introduction
Describe the context of your case study. Introduce the algorithm and possible applications in real world scenarios.
Methodology
Describe the algorithm in more detail (text, pseudocode, flowcharts), with use cases and methods for working with real data sets.
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
Present the resources used for the case study: algorithm, data sets and other references
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
Deep Learning
Data Processing
Visualizations
Examples of applications can be found on:
Datasets
You can use any open dataset. Some common sources include:
Dataset aggregators for Machine Learning projects
Open Datasets
