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ML in Mathematics: Linear Algebra

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Learn linear algebra concepts, including eigenvalues and eigenvectors, and apply them to practical problems using Python and Jupyter notebooks.

Key AI Functions:Eigenvalues And Eigenvectors,Linear Algebra,Transformation Matrix,Linear Algebra

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Description for ML in Mathematics: Linear Algebra

Comprehend the definition of linear algebra and its connection to matrices and vectors, which includes eigenvalues and eigenvectors.

Acquire the skills necessary to interact with vectors and matrices in order to resolve issues.

Utilize linear algebra concepts to solve practical problems, including the analysis of the Pagerank algorithm and the rotation of images.

Utilize Python and Jupyter notebooks to create data-driven applications, including guided coding exercises for novices.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 22

Offered by: On Coursera provided by Imperial College London

Duration: 18 hours (approximately)

Schedule: Flexible

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