Explore the fundamentals of online learning algorithms through a focused lecture that examines performance quantification using the mistake bound approach, covering key concepts like bond models and mistake-driven learning while breaking down the essential goals and methodologies of this machine learning paradigm.
Online Learning and Mistake Bound Analysis - Lecture 6B
Overview
Syllabus
Introduction
Goals
Bond model
Mistake driven learning
Taught by
UofU Data Science
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Foundations of Machine Learning
