The final team project in AAI 501 will give you an opportunity to identify an AI-driven problem, perform a hands-on project, and deliver a report and presentation as a team.
Define a problem on the dataset and describe it in terms of its real-world organizational or business application. The complexity level of the problem should be at least comparable to one of your assignments. The problem may use at least two different types of AI and machine learning algorithms that we have studied in this course, such as Classification, Clustering, and Regression, in an investigation of the analytics solution to the problem. This investigation must include some aspects of experimental comparison. Depending on the problem, you may choose to experiment with different types of algorithms, e.g., different types of classifiers and some experiments with tuning parameters of the algorithms. Alternatively, if your problem is suitable, you may use multiple algorithms (Clustering + Classification, etc.). Note that if there are a larger number of attributes in your selected dataset, you can try some type of feature selection to reduce the number of attributes. You may use summary statistics and visualization techniques to help you explain your findings in this project.
put dataset info here Some rules/tips about choosing AI challenges and data sets for your final projects:
Do not choose the problems that we have already analyzed in the course. The dataset should not be small or made up. For this course, "small" is defined as fewer than 1000 examples in the dataset. Choose a data set that does not require excessive data preprocessing.
data/: Folder containing the raw data.notebooks/: Jupyter notebooks for data analysis, model selection, and evaluation.README.md: This file.
To ensure that you choose an appropriate project, turn in a 1-2 page proposal by the end of Module 3. Use this proposal document to demonstrate that you have completed some background work on your chosen topic. The proposal should begin with a clear and unambiguous statement of your topic and include all of the following:
A brief discussion of the problem and algorithms you intend to investigate and the system you intend to build in doing so. Identification of specific related course topics (e.g., heuristic search, classification, deep learning, NLP, CV, etc.). Examples of expected behaviors of the system or the types of problems the algorithms you investigate are intended to handle.
The issues you expect to focus on. A list of books/papers/articles or other resources you intend to use to inform your project efforts. This list forms the core of your project report reference list in APA 7. Make sure that you will work very closely and constantly communicate with all of your teammates throughout the project in delivering multiple project deliverables every week.
- Clone this repository.
- run
jupyter notebook - Navigate to the
notebooks/directory and open the project notebook. - Follow the instructions in the notebook to run the program.
- Python
- Jupyter Notebook
- Libraries: pandas, numpy
Kim Vierczhalek, Pawan Tahiliani, Will Kencel
This project is licensed under the MIT License.