NumPy Linear Algebra: Exercises, Practice, Solution

NumPy Linear Algebra [19 exercises with solution]

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1. Write a NumPy program to compute the multiplication of two given matrixes.
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2. Write a NumPy program to compute the outer product of two given vectors.
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3. Write a NumPy program to compute the cross product of two given vectors.
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4. Write a NumPy program to compute the determinant of a given square array.
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5. Write a NumPy program to evaluate Einstein's summation convention of two given multidimensional arrays.
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6. Write a NumPy program to compute the inner product of vectors for 1-D arrays (without complex conjugation) and in higher dimension.
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7. Write a NumPy program to compute the eigenvalues and right eigenvectors of a given square array.
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8. Write a NumPy program to compute the Kronecker product of two given mulitdimension arrays.
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9. Write a NumPy program to compute the condition number of a given matrix.
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10. Write a NumPy program to find a matrix or vector norm.
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11. Write a NumPy program to compute the determinant of an array.
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12. Write a NumPy program to compute the inverse of a given matrix.
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13. Write a NumPy program to calculate the QR decomposition of a given matrix.
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14. Write a NumPy program to compute the condition number of a given matrix.
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15. Write a NumPy program to compute the sum of the diagonal element of a given array.
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16. Write a NumPy program to get the lower-triangular L in the Cholesky decomposition of a given array.
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17. Write a NumPy program to get the qr factorization of a given array.
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18. Write a NumPy program to compute the factor of a given array by Singular Value Decomposition.
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19. Write a NumPy program to calculate the Frobenius norm and the condition number of a given array.
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