Machine learning

Subjects

Features

Master IB Computer Science Machine learning with flashcards created by examiners and strictly aligned with the syllabus.

A4.1

Machine learning fundamentals

Learning approaches, Real-world applications, Processing, Storage, Scalability

A4.2

Data preprocessing

Data cleaning, Missing data, Normalization, Standardization, Feature selection, Dimensionality reduction

A4.3

Machine learning approaches

Regression, Classification, Model evaluation, Clustering, Association rules, Reinforcement learning, Genetic algorithms, Neural networks, Model selection

A4.4

Ethical considerations

Training-data bias, Fairness, Accountability, Online communication, Privacy, Emerging technologies

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