IB Computer Science Topic A4.3 Machine Learning Approaches (HL) covers syllabus content. Use these notes, questionbank, flashcards, and lessons to review the topic, practise exam questions, and move between notes, videos, flashcards, and lessons where available.
What this topic covers
A4.3.1 Linear Regression in Predicting Continuous Outcomes (HL only)
A4.3.2 Classification Techniques in Supervised Learning (HL only)
A4.3.3 Role of Hyperparameter Tuning in Supervised Learning Algorithms (HL only)
A4.3.4 Clustering Techniques in Unsupervised Learning (HL only)
A4.3.5 Learning Techniques Using the Association Rule Used in Large Data Sets (HL only)
A4.3.6 Agents Learning to Make Decisions (HL only)
A4.3.7 Application of Genetic Algorithms (HL only)
A4.3.8 Structure and Function of ANNs (HL only)
A4.3.9 Design of CNNs (HL only)
A4.3.10 Model Selection and Comparison in Machine Learning (HL only)