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Related lectures (32)

Kernel Regression: Basics and Applications Log in to Mediaspace to watch this video

Explores kernel regression, the curse of dimensionality, and random features in neural networks.

Kernel Ridge Regression: Equivalence, Representer Theorem, and Kernel Trick Log in to Mediaspace to watch this video

Explores Kernel Ridge Regression, the Representer Theorem, and the Kernel Trick in machine learning.

Feature Expansion and Kernels Log in to Mediaspace to watch this video

Covers feature expansion, kernels, SVM, and nonlinear classification in machine learning.

Support Vector Machines: Kernel Tricks Log in to Mediaspace to watch this video

Explores kernel tricks in support vector machines for efficient computation in high-dimensional spaces without explicit transformation.

Kernel Trick: Understanding Machine Learning Log in to Mediaspace to watch this video

Explores the kernel trick in machine learning, enabling high-dimensional operations without explicit coordinate calculations.

Kernel Regression: K-nearest Neighbors Log in to Mediaspace to watch this video

Covers the concept of kernel regression and K-nearest neighbors for making data linearly separable.

Darcy Problem: Discretisations and Coercivity Log in to Mediaspace to watch this video

Covers the Darcy problem, focusing on discretisations and the concept of coercivity.

Feature Selection, Kernel Regression, Neural Networks Playground Log in to Mediaspace to watch this video

Covers feature selection, kernel regression, and neural networks through exercises.

Dimensionality Reduction: PCA & LDA Log in to Mediaspace to watch this video

Covers PCA and LDA for dimensionality reduction, explaining variance maximization, eigenvector problems, and the benefits of Kernel PCA for nonlinear data.

Neural Networks: Random Features and Kernel Regression Log in to Mediaspace to watch this video

Explores random features in neural networks and kernel regression using stochastic gradient descent.

Incremental Regression: LWPR Log in to Mediaspace to watch this video

Explores incremental learning with LWPR, discussing challenges, synthetic data, real-world applications, and the LWPR algorithm.

Support Vector Machines: Kernel SVM Log in to Mediaspace to watch this video

Explores non-linear SVM using kernels for data separation in higher-dimensional spaces, optimizing training with kernels to avoid explicit transformations.

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