Artificial Intelligence (AI) Laboratory (CST3170)
- Utilised the ID3 algorithm and a dataset to split a decision tree in a way to categorise a patient with the correct lens type for their eyes.
- Implemented linear categorisers, self-organising maps, state-space search (missionaries and cannibals’ problem), and case-based reasoning (Euclidean distances, k-nearest neighbours) algorithms thus far.
- Leveraged Knowledge: In AI, categorisers, deep neural nets, concepts of linear algebra and calculus.
Below you can find a table listing the topics of each laboratory.
The '✅' will give you more information such as how I approached achieving the 'Topic'
| Laboratory Week | Topic | Link to repository |
|---|---|---|
| 1 | 2D Arrays | ✅ |
| 2 | Linear Categoriser | ✅ |
| 3 | Categorisation with Decision Trees | ✅ |
| 4 | State-Space Search | ✅ |
| 5 | Genetic Algorithm | ✅ |
| 6 | Cased Based Reasoning | ✅ |
| 7 | Prolog Language | ✅ |
| 8 | Self Organising Maps | ✅ |
| 9 | - | - |
| 10 | - | - |
| 11 | - | - |
| 12 | Multi Layer Perceptron | ✅ |
| 13 | Eight Queens | ✅ |
| 14 | Chatbot | ✅ |
| 15 | Processing with Neurons | ✅ |
| 16 | Simple Vision | ✅ |
| 17 | Utility | ✅ |
| 18 | Support Vector Machines | ✅ |
| 19 | - | - |
| 20 | XML | ✅ |
| 21 | Parallel Sort | ✅ |
| 22 | Rule Based Systems | ✅ |
| 23 | Search and Search Spaces | ✅ |
| 24 | - | - |