ESE 5450 Data Mining: Learning from Massive Datasets

Short Description

Many scientific and commercial applications require us to obtain insights from massive, high-dimensional data sets. In this graduate-level course, students will learn to apply, analyze and evaluate principled, state-of-the-art techniques from statistics, algorithms and discrete and convex optimization for learning from such large data sets. The course both covers theoretical foundations and practical applications.

Portfolio Building Course

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Pre-Requisites

CIT 5920 Mathematical Foundations of Computer Science & CIS 5150 Fundamentals of Linear Algebra & Optimization (Math for Machine Learning)

Content

Many scientific and commercial applications require us to obtain insights from massive, high-dimensional data sets. In this graduate-level course, students will learn to apply, analyze and evaluate principled, state-of-the-art techniques from statistics, algorithms and discrete and convex optimization for learning from such large data sets. The course both covers theoretical foundations and practical applications.

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