Artificial Intelligence - 2024/25

Notes and Examples

Overview of AI Concepts

• Overview of AI
• Machine Learning Basics
• Neural Networks Foundations
• Generative and Agentic AI

Basic Setup and Tools

• Overview of technologies for Python AI development

• Repo on Python IDEs and Syntax

• NumPy

  • NumPy
  • Algebra with NumPy
    • Examples: Lists vs NumPy Array Manipulation

• Pandas

  • Series and DataFrame structure
  • DataFrame operations
  • DataFrame advanced transformations
    • Example: DataFrame from different structures

Tic-Tac-Toe Example (basics/minimax/oop/qlearning)

Classic Algorithms of Machine Learning

• Timeline of Key Algorithms
• Linear Regression
• Logistic Regression
• K-means
• K-Nearest Neighbors (KNN)
• Decision Trees
• Q-Learning (Reinforcement Learning)
  • Frozen Lake Example
  • Bellman Equation In Depth
• Random Forests

Basic Machine Learning Workflows

• Overfitting and Train/Test Split
• Diabetes Regression
• Diabetes Classification
• California Housing Prices - Simple Linear Regression
• Iris Dataset (Classification):
  • Data Structure and EDA
  • Logistic Regression Workflow
  • Pipelines and Validation
• MNIST with SVM - Detailed Classification Evaluation
• Clustering and PCA on digits
• Clustering of Iris

Complete Projects

• California Housing Prices - End-to-End ML Regression Project
• Thyroid Diseases - Classification
• King County House Sales - Regression

Additional External Resources

• Data Science cheatsheet
• Notes on Bayesian Probability
• Basic Mathematics for Machine Learning