Omer-l / CST3170_Laboratory

Classification of items with a Line, Decision Tree. State-Space Search, Genetic Algorithms, Case-Based Reasoning, Self-Organising Maps and much more!

CST3170_Laboratory

During my third year as an undergraduate, I took a module on Artificial Intelligence.

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	-	-