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Related lectures (30)

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Kernel Methods: Machine Learning

Covers Kernel Methods in Machine Learning, focusing on overfitting, model selection, cross-validation, regularization, kernel functions, and SVM.

Optimal Linear Response: Stochastic Dynamical Systems

Explores optimal linear response for stochastic dynamical systems, addressing perturbations and mixing rate optimization.

Kernel Regression: K-nearest Neighbors

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

Linear Applications in 3D: Rank Theorem

Explains the Rank Theorem for linear applications in 3D space and its implications.

Practical Session Microscopes

Covers practical aspects of microscopes, including dark field images, resolution, and a report assignment.

Hensel's Lemma Application

Discusses the application of Hensel's lemma in determining nth roots and elements that are nth powers.

The inhomogeneous Ising chain

Covers the inhomogeneous Ising chain, Gibbs measures, and the Borel-Cantelli lemma.

MicroC/OS-II: Real-Time Kernel Overview

Provides an overview of MicroC/OS-II, a real-time kernel with multitasking capabilities and deterministic functions, covering topics such as task management, kernel, and intertask communication.

Data Intensive Applications and Systems: Installation and Configuration

Covers the installation and configuration process of data-intensive applications and systems.

Quantitative Imaging for Civil Engineers

Covers quantitative imaging for civil engineers, focusing on image representation, formats, color encoding, and quality assessment.