Module Learning Outcomes

Module Learning Outcomes

By the end of the module, students are expected to:

• Explain the motivation to study machine learning.
• Differentiate between supervised and unsupervised learning.
• Differentiate between classification and regression problems.
• Explain machine learning terminology such as features, targets, training, and error.
• Use DummyClassifier/ Dummy Regressor as a baseline for machine learning problems.
• Explain the .fit() and .predict() paradigm and use .score() method of ML models.

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