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Linear Algebra in 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

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Description for Linear Algebra in ML & Data Science

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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