Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Home

Lecture

Support Vector Machines: Non-Linear Data Mapping

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (46)

Linear Models for Classification: Multi-Class Extensions Log in to Mediaspace to watch this video

Covers linear models for multi-class classification, focusing on logistic regression and evaluation metrics.

Non-Convex Optimization: Techniques and Applications Log in to Mediaspace to watch this video

Covers non-convex optimization techniques and their applications in machine learning.

Nonlinear Machine Learning: k-Nearest Neighbors and Feature Expansion Log in to Mediaspace to watch this video

Covers the transition from linear to nonlinear models, focusing on k-NN and feature expansion techniques.

Neural Networks Recap: Activation Functions Log in to Mediaspace to watch this video

Covers the basics of neural networks, activation functions, training, image processing, CNNs, regularization, and dimensionality reduction methods.

Regression: Interactive Lecture Log in to Mediaspace to watch this video

Covers linear regression, weighted regression, locally weighted regression, support vector regression, noise handling, and eye mapping using SVR.

Convex Optimization Tutorial: KKT Conditions Log in to Mediaspace to watch this video

Explores KKT conditions in convex optimization, covering dual problems, logarithmic constraints, least squares, matrix functions, and suboptimality of covering ellipsoids.

Statistics for Civil Engineering Log in to Mediaspace to watch this video

Covers the fundamentals of statistics, exploring probabilistic models, variability, uncertainty, and data collection.

Machine Learning: Supervised and Unsupervised Learning Techniques Log in to Mediaspace to watch this video

Covers supervised and unsupervised learning techniques in machine learning, highlighting their applications in finance and environmental analysis.

Estimation Example: Least Square Estimation Log in to Mediaspace to watch this video

Covers the concept of least square estimation and its real-world applications.

Linear Regression Basics Log in to Mediaspace to watch this video

Covers the basics of linear regression, instrumental variables, heteroskedasticity, autocorrelation, and Maximum Likelihood Estimation.

Microwaves Interaction: Matter & Applications Log in to Mediaspace to watch this video

Explores microwaves' interaction with matter, covering heating effects, biological impacts, and safety standards.

Linear Algebra: Normal Equations and Symmetric Matrices Log in to Mediaspace to watch this video

Explores normal equations, pseudo-solutions, unique solutions, and symmetric matrices in linear algebra.

Clustering & Density Estimation Log in to Mediaspace to watch this video

Covers clustering, PCA, LDA, K-means, GMM, KDE, and Mean Shift algorithms for density estimation and clustering.

Noise in Electronics: Fundamentals and Applications Log in to Mediaspace to watch this video

Explores noise in electronics, covering average power, signal-to-noise ratio, deterministic and random signals, and noise amplification.

Support Vector Machines: Basics and Applications Log in to Mediaspace to watch this video

Covers the basics of Support Vector Machines, including linear separability, hyperplanes, margins, and non-linear SVM with kernels.

Regression Trees and Ensemble Methods in Machine Learning Log in to Mediaspace to watch this video

Discusses regression trees, ensemble methods, and their applications in predicting used car prices and stock returns.

Overfitting in Supervised Learning: Case Studies and Techniques Log in to Mediaspace to watch this video

Addresses overfitting in supervised learning through polynomial regression case studies and model selection techniques.

Kernel Methods in Machine Learning: Kernel Regression and SVM Log in to Mediaspace to watch this video

Discusses kernel methods in machine learning, focusing on kernel regression and support vector machines, including their formulations and applications.

Understanding Ideal Detectors: Theory and Applications Log in to Mediaspace to watch this video

Provides an overview of ideal detectors, focusing on their theory, noise limitations, and performance metrics in optical detection systems.

Untitled Log in to Mediaspace to watch this video

Page 2 of 3