Introduction to Artificial Intelligence

• Reading 01: Search Algorithms
• Reading 02: Constraint Satisfaction, Alpha-Beta Pruning
• Reading 03: K-Nearest Neighbors, Decision Trees
• Reading 04: Bayes Theorem, Markov Chains, Hidden Markov Models
• Reading 05: Regularization, Perceptron
• Reading 06: Logistic Regression, Gradient Descent
• Reading 07: SVMs
• Reading 08: Clustering, PCA, Model Evaluation
• Reading 09: Neural Networks, Gradient Descent, Backpropagation
• Reading 10: Convolutional Neural Networks
• Reading 11: Recurrent Neural Networks
• Reading 12: Transformers, Attention
• Reading 13: Reinforcement Learning