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Related lectures (32)

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Common Sequences Operations

Covers common operations on sequences like lists and tuples, including slicing, extending, and replacing elements.

Linear Transformations: Matrices and Kernels

Covers linear transformations, matrices, kernels, and properties of invertible matrices.

Unitary Representations: Schur's Lemma

Explains Schur's Lemma on unitary representations and their irreducibility and invariance properties.

Feature Maps and Kernels

Covers feature maps, Representer theorem, kernels, and RKHS in machine learning.

Regression: Exercises

Covers exercises on regression functions using RLS, WLS, and LWR.

Coq Workshop: Inductive Data Types and Proofs

Covers the definition of an inductive data type in Coq and how to build proofs interactively using tactics.

Support Vector Machines: Kernel SVM

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

Linear Algebra in 3D: Images and Kernels

Explores linear applications in 3D, emphasizing images, kernels, and solution uniqueness in systems.

Linear Transformations: Kernels and Images

Covers kernels and images of linear transformations between vector spaces.

Python Programming Basics

Covers the basics of Python programming, focusing on flow control structures, interactive mode, script mode, and variables.