Explore core ML concepts and algorithms like supervised learning, concept learning, Find-S, and Candidate Elimination.
What you will learn
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Understand well-posed learning problems and key components of a machine learning system.
Analyze concept learning as a search problem and apply it to hypothesis spaces.
Implement and evaluate the Find-S algorithm for concept learning tasks.
Apply the Candidate Elimination algorithm to refine hypothesis spaces based on training data.
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