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Topic overview
Learn the foundations of Machine Learning.
Machine Learning connects features, labels, training, validation, common models, and generalization with practical decisions and tasks. Guided examples, comparison, practice, and feedback help learners apply these ideas to building and evaluating predictive systems without confusing fit with usefulness. The goal is to make each step easier to explain, check, and improve.
Learning outcomes for Machine Learning
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1
Explain the main ideas and vocabulary involved in features, labels, training, validation, common models, and generalization
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2
Follow a repeatable process for building and evaluating predictive systems without confusing fit with usefulness
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3
Compare examples, identify common mistakes, and improve an approach
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4
Complete an independent machine learning task and reflect on the result
5 lessons
2 hrs 30 min 
