Kernel panic

Related lectures (30)

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Covers the definition of linear applications in IR³ to R³ and explores examples and properties.

Covers the determination of a matrix associated with a linear transformation and the concepts of kernel and image.

Covers data manipulation and exploration using Python with a focus on visualization techniques.

Delves into the Rank Theorem's implications for linear transformations and mappings.

Covers the calculation of dimensions in linear algebra, focusing on determining the dimension of the kernel of a given matrix.

Explores the Hopf formula in cohomology groups, emphasizing the 4-term exact sequence and its implications.

Introduces singular homology, defining singular simplices and explaining the chain complex construction.

Covers the basics of linear mapping and coordinate systems.

Covers the basics of object-oriented programming in Python, including objects, classes, inheritance, and input/output handling.

Explores matrix representations of linear applications, including change of basis and invariants.