Mathematics for ML: Linear Algebra

Mathematics for ML: 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

Description for Mathematics for ML: Linear Algebra

Features of Course

  • 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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