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Advanced Vision and Learning Lab (AVLL)

Texas A&M University College of Engineering

ECEN 758

Course Prerequisites

  • Graduate standing
  • Recommended: Familiarity with programming language Python and basic knowledge of multivariate calculus, statistical inference, and linear algebra

Course Description

  • A broad overview of data mining, integrating related concepts from machine learning and statistics; exploratory data analysis, pattern mining, regression, clustering, and classification; with applications to scientific and online data. Cross Listings: CSCE 676 and STAT 639

Course Objectives

  • Acquire knowledge of foundations and application of methods in data mining and data analysis; prepare students to use methods and tools of data science in research in methods or applications.
  • Conduct exploratory data analysis including visualization and summarization
  • Apply selected unsupervised machine learning methods to data analytical problems
  • Apply selected supervised machine learning methods to data analytical problems
  • Select appropriate machine learning method applicable to common problem types
  • Understand usage rationale, underpinnings, and limitations of machine learning methods
  • Apply common libraries and tools to data analytical problems

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