EEC3501 Machine Learning Lecture 8 PDF
Document Details
Uploaded by ManeuverableSanity7698
Tags
Related
- Elements of Machine Learning & Data Science Lecture Notes 2024/25 PDF
- DST301 Artificial Intelligence Applications Lecture 02 - Machine Learning PDF
- Machine Learning Lecture Notes PDF
- Machine Learning Lecture Notes (PDF)
- AI216 Machine Learning and Pattern Recognition PDF Fall 2024/2025 Lecture Notes
- Machine Learning and Bioinformatics Lecture Notes PDF
Summary
This lecture covers concepts in Machine Learning, specifically focusing on separating hyperplanes, optimal separating hyperplanes, geometry, maximizing margins, optimization problems, and non-separable data. It also includes sections on maximizing margins, soft margins, hinge loss, and concludes with a thanks note.
Full Transcript
EEC3501 Machine Learning Separating Hyperplane Optimal Separating Hyperplane Geometery Maximizing Margin Optimization Problem Non-Separable data Maximizing Margin Soft Margin Hinge Loss Thanks! Do you have any questions?
EEC3501 Machine Learning Separating Hyperplane Optimal Separating Hyperplane Geometery Maximizing Margin Optimization Problem Non-Separable data Maximizing Margin Soft Margin Hinge Loss Thanks! Do you have any questions?
