Support Vector Machines
Computer Science · University of Applied Sciences · Machine Learning
This unit introduces the concepts and applications of Support Vector Machines (SVMs), a powerful machine learning algorithm for classification and regression. Students will learn about SVM models, kernel functions, and their use in various real-world scenarios.
Zum Üben gibt es 57 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Introduction to Support Vector Machines
- Linear SVMs
- Nonlinear SVMs and Kernel Functions
- SVM Training and Optimization
- SVM Applications in Classification
- SVM Applications in Regression
- Overfitting and Regularization in SVMs
- SVM Parameter Tuning and Evaluation
Stichworte
- SVM
- Kernel Functions
- Classification
- Regression
- Hyperplane
- Margin
- Support Vectors
- Overfitting
- Regularization