Dive deep into advanced concepts of the Perceptron algorithm through a comprehensive lecture that explores practical variants and the fundamental mistake bound theorem. Learn how these essential machine learning concepts work together to form the foundation of neural networks and modern classification techniques. Expand your understanding of machine learning theory with detailed explanations and practical applications over 78 minutes of in-depth instruction.
Perceptron Algorithm and Mistake Bound Theorem - Lecture 9
Overview
Syllabus
Lecture 9: Perceptron (continued)
Taught by
UofU Data Science
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