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ABOUT THE COURSE
This course helps you to understand the vectors in different dimensions and their linear transformation to some other domain, matrix theory and various properties of matrices and its transformations, Eigenvalues and Eigenvectors and their role in dimensionality reduction and the applications of linear algebra for AI and ML.COURSE OBJECTIVES
Upon successful completion of the course, the learner will be able to :In this topic, you will learn about the multidimensional vector space and its various representations. You will also understand the transformations between different domains.
In this topic, you will learn about Subspaces, span and Basis of a vector and how it reduces the complexity of representing the vectors.
In this topic, you will learn about Grouping multiple vectors to form matrices and various types of matrices and its properties.
In this topic, you will learn about how to derive Eigenvalues and Eigenvectors from the matrices and how they are used to reduce dimension.
In this topic, you will learn about how to find the inner product of the matrix and its properties and short cuts to find it. You will also learn how Linear Algebra is used in the field of AI and ML.
You can opt for the following courses once you complete your ongoing course
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