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Foundational ML concepts, data preparation, and model evaluation.
Review supervised and unsupervised learning concepts.
Understand feature engineering and data preparation.
Learn how to judge model quality and generalization.
Create a base for future deep learning and MLOps topics.
Cleaning and feature shaping
Classical machine learning methods
Metrics and validation patterns
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Back to LearnPractical examples that connect the category to real-world implementation.
Scalable retrieval system for querying enterprise knowledge bases
Useful starting points and supporting materials for this category.