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Related lectures (32)

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.

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.

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.

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.

Learning the Kernel: Convex Optimization Log in to Mediaspace to watch this video

Explores learning the kernel function in convex optimization, focusing on predicting outputs using a linear classifier and selecting optimal kernel functions through cross-validation.

Discrete Pressure Modes in Lecture 4 Log in to Mediaspace to watch this video

Explores discrete pressure modes and their impact on system analysis.

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

Covers feature expansion, kernels, and K-nearest neighbors, including non-linearity, SVM, and Gaussian kernels.

Feature Expansion and Kernel Methods Log in to Mediaspace to watch this video

Explores feature expansion, kernel methods, 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 K-means: Iterative Clustering Algorithm Log in to Mediaspace to watch this video

Explores the Kernel K-means iterative clustering algorithm and its influence on cluster density and point proximity.

Atomic Descriptors: Symmetry and Locality Log in to Mediaspace to watch this video

Explores atomic descriptors, emphasizing symmetry, locality, and the challenges of incorporating electrostatics in machine learning models for chemistry.

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