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Overview
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Dive into a comprehensive tutorial on Linear Discriminant Analysis (LDA) and its applications in machine learning. Explore the core concepts of discriminant analysis, including its use in dimension reduction, pattern classification, and decision-making processes across various industries. Learn about the goals of discriminant analysis, such as profiling, differentiation, and classification. Engage with a practical exercise on Fisher's discriminant analysis to solidify your understanding. Discover how data scientists and business analysts can leverage this powerful tool to design innovative solutions for corporate challenges. Gain valuable insights into the mathematics behind LDA and its real-world applications in finance, marketing, and medical science.
Syllabus
Introduction.
Agenda.
Discriminant analysis.
Goals of Discriminant analysis.
Exercise on the application of Fisher’s discriminant analysis.
Summary.
Taught by
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