Linear Algebra for ML & Data Science

Linear Algebra for ML & Data Science

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Apply linear algebra concepts like linear independence, rank, singularity, eigenvalues, and eigenvectors to analyze data and solve machine learning problems using standard vector and matrix operations.

Key AI Functions:Eigenvalues And Eigenvectors,Linear Equation,Determinants,Machine Learning,Linear Algebra

Description for Linear Algebra for ML & Data Science

Features of Course

  • Use the concepts of linear independence, rank, and singularity to identify the properties of data represented as vectors and matrices.
  • Utilize standard vector and matrix algebra operations, including the dot product, inverse, and determinants.
  • Apply the concepts of eigenvalues and eigenvectors to machine learning problems and express specific categories of matrix operations as linear transformations.
  • Level: Beginner

    Certification Degree: Yes

    Languages the Course is Available: 22

    Offered by: On Coursera provided by DeepLearning.AI

    Duration: 34 hours (approximately)

    Schedule: Flexible

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