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Bharani Kumar Depuru is a well known IT personality from Hyderabad. He is the Founder and Director of AiSPRY and 360DigiTMG. Bharani Kumar is an IIT and ISB alumni with more than 18+ years of experience, he held prominent positions in the IT elites like HSBC, ITC Infotech, Infosys, and Deloitte. He is a prevalent IT consultant specializing in Industrial Revolution 4.0 implementation, Data Analytics practice setup, Artificial Intelligence, Big Data Analytics, Industrial IoT, Business Intelligence and Business Management. Bharani Kumar is also the chief trainer at 360DigiTMG with more than Ten years of experience and has been making the IT transition journey easy for his students. 360DigiTMG is at the forefront of delivering quality education, thereby bridging the gap between academia and industry.
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Answer - b) det(A - λI) = 0
"Eigen vector of a matrix A is a vector represented by a matrix X. The product of matrix A and vector X, the direction of the output matrix remains same as vector X. formula: AX = λX where, A is any arbitrary matrix, λ are Eigen values and, X is an Eigen vector. The equation used to find the Eigenvalues of a matrix is called characteristic equation of the matrix. Also known as characteristic polynomial. For a square matrix A and, λ being any scalar, the characteristic equation of a matrix A is '|A - λI| = 0' - The equation hints that the matrix (A - λI)X = 0 takes X into the 0 vector. This also means that the (A - λI) will not have an inverse so that its determinant must be 0. - det(A - λI) = 0 is the characteristic of the matrix - The trace of a square matrix - Tr(A) = Sum(diagonal elements)"
Answer - d) Square Matrix
"C.Every square matrix with real or complex numbers satisfies its characteristic (eigen values) equation. A square matrix when transformed into a polynomial equation (det(A - λI)) can be equated to 0. |A - λI| = 0 example: A = 1 2 -1 2 A - λI [1 2 [1 0 -1 2] - λ* 0 1] |A - λI| will be a polynomial equation with degree equal to n (A is a n*n matrix) The polynomial equation: λ^2 - 3λ + 4 (degree 2, which is equal to dimension of Matrix A 2*2) equals to zero. λ^2 - 3λ + 4 = 0"
Answer - d) All the Above.
"The process of representing a square matrix and converting it into a special type of diagonal matrix that shares the same fundamental properties as the underlying matrix. Diagonalizing can also be seen as a process of finding the matrix's eigenvalues, which are the diagonal elements of the matrix."
Answer - d) 1x2 matrix
"A square matrix has an equal number of rows and columns,. i.e., the dimension of a square matrix is n x n. Therefore, option D) 1x2 matrix is not a square matrix as it has different number of rows and columns."
Answer - a) [[1,0,0], [0,2,0], [0,0,3]]
"A diagonal matrix is a square matrix where all the elements outside the main diagonal are zero. Therefore, option a) is a diagonal matrix."
Answer - a) 3x2
"To multiply two matrices, the number of columns in the first matrix must be equal to the number of rows in the second matrix. Here, A has 3 rows and 3 columns, and B has 3 rows and 2 columns. So, the resulting matrix AB will have 3 rows and 2 columns."
Answer - c) It is equal to the sum of its diagonal elements
"The determinant of a matrix is a scalar value that can be positive, negative, or zero. It is not equal to the sum of its diagonal elements. However, the sum of the diagonal elements of a matrix is known as the trace of the matrix."
Answer - c) It does not exist
"If the determinant of a matrix A is zero, then its inverse does not exist. This is because the inverse of a matrix can be found only if the determinant is not equal to zero."
Answer - d) Octagonal matrix
"Octagonal matrix is not a type of matrix. The other options are types of matrices. "
Answer - c) [[1,2,3], [4,5,6]]
"A square matrix has the same number of rows and columns. The matrices in options a), b), and d) are all square matrices, whereas the matrix in option c) is not a square matrix."
"The product of two matrices A and B is defined only if the number of columns of A is equal to the number of rows of B. Here, A has 4 columns and B has 4 rows, so their product AB will have 3 rows and 2 columns."
Answer - b) [[2,0], [0,2]]
"A scalar matrix is a diagonal matrix where all the diagonal elements are equal. The matrix in option b) is a scalar matrix with diagonal elements equal to 2."
Answer - a) [[1,2], [2,1]]
"A matrix is symmetric if it is equal to its transpose. The matrix in option a) is symmetric because it is equal to its transpose."
Answer - c) Cross product
"Cross product is a type of operation that is defined only for vectors and not for matrices. The other options are all types of matrix multiplication."
Answer - a) Cross product
"A matrix is invertible if its determinant is not equal to zero. The determinant of matrix a) is equal to -2, which is not equal to zero, so it is invertible. However, the determinant of matrix b) is equal to 1, the determinant of matrix c) is equal to 0, and the determinant of matrix is equal to 0. Therefore, matrices , c), and d) are not invertible.>"
Answer - a) [[1,2,3]]
"A row matrix is a matrix with only one row. The matrix in option a) is a row matrix."
Answer - b) [[0,1], [-1,0]]
"A matrix is skew-symmetric if it is equal to the negative of its transpose. The matrix in option b) satisfies this property and is therefore skew-symmetric."
Answer - d) The product of a matrix and its inverse is equal to the identity matrix
"If a matrix A is not invertible, then it does not have an inverse. Therefore, option d) is not a property of the inverse of a matrix."
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