bestgogo/msc_ai_sem1

Coursework Assignment and work

QMUL MSc in AI course and lecture repo

Courses Undertaken

1. ECS7006 Artifical Intelligence in Games
2. ECS708 Machine Learning
3. ECS766 Data Mining
4. ECS763 Natural Language and Processing

Course Content

ECS7006 Artifical Intelligence in Games

• Decision Making (DT, FSM, BT, GOAP)
• Search (BFS, DFS, A*, MCTS, RHEA)
• Basics of Reinforcement Learning (MDP)
• Reinforcement Learning I (DP, MC, TDL)
• Reinforcement Learning II (Q-Learning, MCC, UCT)
• Game Theory (Nash, Minimax, αβ)
• Procedural Content Generation I
• Procedural Content Generation II
• Machine Learning for Games
• Deep Learning

ECS708 Machine Learning

• Basic Probability
• Bayesian Reasoning
• Linear Regression
• Logistic Regression
• Neural Networks
• Clustering
• Density Estimation & EM Algorithm
• Hidden Markov Models (HMMs)
• Dimensionality Reduction (PCA, ICA)

ECS766 Data Mining

• Regression
• Classification
• Features and dimensionality
• Clustering
• Anomaly detection
• Association mining
• Plus practical considerations, advanced topics, applications.

ECS763 Natural Language and Processing

• Statistical methods 1: language modelling
• Statistical methods 2: classification/regression
• Statistical methods 3: sequence modelling (HMMs, CRFs)
• Syntax 1: generative and logical grammars
• Syntax 2: dependency and probabilistic grammars
• Syntax 3: limitations of syntax, tools and TreeBanks
• Semantics 1: formal and distributional semantics
• Semantics 2: compositional distributional semantics
• Discourse & Dialogue 1: coreference resolution
• Discourse & Dialogue 2: dialogue models and systems