A1 Computer fundamentals
A2 Networks
A3 Databases
A4 Machine learning
A4.1 Machine learning fundamentals
A4.2 Data preprocessing (HL only)
A4.3 Machine learning approaches (HL only)
A4.4 Ethical considerations
B1 Computational thinking
B2 Programming
B3 Object-oriented programming
B4 Abstract data types (HL only)
Browse syllabus-aligned notes for A4.3 Machine Learning Approaches. Open each subtopic for focused explanations, examples, and summaries.
A4.3.1 Linear Regression in Predicting Continuous Outcomes (HL only)
9 minute read
A4.3.2 Classification Techniques in Supervised Learning (HL only)
3 minute read
A4.3.3 Role of Hyperparameter Tuning in Supervised Learning Algorithms (HL only)
A4.3.4 Clustering Techniques in Unsupervised Learning (HL only)
7 minute read
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)
6 minute read
A4.3.7 Application of Genetic Algorithms (HL only)
10 minute read
A4.3.8 Structure and Function of ANNs (HL only)
11 minute read
A4.3.9 Design of CNNs (HL only)
A4.3.10 Model Selection and Comparison in Machine Learning (HL only)