Support Vector Machines (SVM) — Roadmap Step & Resources
Finding the maximum-margin boundary between classes, with kernels for non-linear data
- Level: intermediate
- Estimated time: 2 days
- Roadmap: Machine Learning
Before this step
Interview questions
- What role does the kernel trick play in SVMs?
Study resources
- Support Vector Machines (Video) — Informative resource that provides detailed insights and practical knowledge about Support Vector Machines.
- Support Vector Machines, Clearly Explained!!! (Video) — StatQuest's widely-loved explanation of SVMs and the kernel trick.
- Support Vector Machines (Article) — The official scikit-learn documentation for SVM classifiers.
- StatQuest: Support Vector Machines Part 2 - The Polynomial Kernel (Class Central index) (Video) — StatQuest: Support Vector Machines Part 2 - The Polynomial Kernel (Class Central index) — resource aligned with Support Vector Machines.
- Understanding F1 Score, Accuracy, ROC-AUC & PR-AUC Metrics — Deepchecks (Article) — Understanding F1 Score, Accuracy, ROC-AUC & PR-AUC Metrics — Deepchecks — resource aligned with Support Vector Machines.
- NPTEL Artificial Intelligence: Search Methods for Problem Solving, IIT Madras (Article) — NPTEL AI course covering state-space search, BFS, DFS, heuristic search, A*, AO*, CSP, rule systems and game playing.
Part of
- Supervised Learning: Classification — section
- Machine Learning roadmap — the full learning path