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Data Mining Lecture Summary Data Science Exam Prep Guide 2025/ 2026

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Master the fundamentals of data mining with solution using this comprehensive 2025/ 2026 lecture summary. Includes key concepts covering data preprocessing, pattern discovery, classification, clustering, association rules, and predictive modeling designed to improve analytical understanding, strengthen exam performance, and support success in data science, machine learning, and analytics courses.

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Institution
Data Mining
Course
Data Mining

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Data Mining – lecture summary.pdf Data Mining – lecture summary.pdf Data Mining – lecture summary.pdf




Data Mining – lecture
summary




Data MiningGuidehttps://www.stuvia.com/dashboard!@_)#*)(@$)($@*($@)($@*_
– lecture summary.pdf Data Mining – lecture summary.pdf Data Mining – lecture summary.pdf

, Data Mining.pdf Data Mining.pdf Data Mining.pdf


Terms in this set (23)



Data mining - science of extracting useful info from large datasets
- discovering relationships between parts of a dataset
- relationships and summaries = models or patterns
- "trend" used to describe patterns that occur or change over time
- difference between data mining and machine learning


- Data mining relates to:
databases,
statistics,
AI,
machine learning,
pattern recognitions


- cyclical: starts w/ data, mining leads to discovery, leads to action/deployment,
leads to new data, and the cycle continues


Machine Learning - process of training an algorithm on existing dataset to discover relationships
- using result to analyze NEW data




Data Mining.pdf Data Mining.pdf Data Mining.pdf

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Data Mining
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