A4 Machine learning

A4.3 Machine learning approaches (HL only)

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Computer Science
Notes
10

Notes

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  1. 01A4.3.2 — Classification: K-Nearest Neighbours and Decision Trees
  2. 02A4.3.3 — Hyperparameter Tuning and Evaluating Supervised Models
  3. 03A4.3.8 — Artificial Neural Networks: Perceptrons to Multi-Layer Networks
  4. 04A4.3.10 — Model Selection and Comparison in Machine Learning
  5. 05A4.3.7 — Genetic Algorithms: Evolution as an Optimiser
  6. 06A4.3.5 — Association Rule Learning: Uncovering Relationships in Data
  7. 07A4.3.9 — Convolutional Neural Networks: Learning Spatial Hierarchies
  8. 08A4.3.6 — Reinforcement Learning: Agents, Rewards and Policies
  9. 09A4.3.1 — Linear Regression: Predicting Continuous Outcomes
  10. 10A4.3.4 — Clustering: Grouping Data by Similarity

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