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NumPy Performance Optimization Exercises with Solutions

NumPy Performance Optimization Exercises [ 20 exercises with solution]

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1. Write a NumPy program that creates a large 1D array and write a function to calculate the sum of its elements using a for loop. Then, optimize it using NumPy's built-in functions.
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2. Write a NumPy program that generate two large NumPy arrays and write a function to perform element-wise addition using a for loop. Optimize it with vectorized operations.
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3. Write a function to compute the dot product of two large NumPy arrays using a nested for loop. Then, optimize it using NumPy's dot() function.
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4. Write a NumPy program to create a large 2D NumPy array and write a function to calculate the row-wise mean using a for loop. Optimize it using vectorized operations.
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5. Write a NumPy program to create a large NumPy array and write a function to calculate the standard deviation of its elements using a for loop. Optimize it using NumPy's built-in functions.
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6. Write a NumPy program that creates a function to transpose a large 2D NumPy array using nested for loops. Optimize it using NumPy's transpose() function.
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7. Write a NumPy program that creates a function to compute the element-wise multiplication of two large 2D arrays using nested for loops. Optimize it using NumPy's vectorized operations.
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8. Write a NumPy program to generate a large 3D NumPy array and write a function to compute the sum of all elements using nested for loops. Optimize it using NumPy's built-in functions.
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9. Write a NumPy program to generate a large NumPy array and write a function to find the maximum element using a for loop. Optimize it using NumPy's built-in functions.
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10. Write a NumPy program that creates two large 1D NumPy arrays and write a function to compute their element-wise division using a for loop. Optimize it with vectorized operations.
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11. Write a NumPy program that creates a function to calculate the cumulative sum of a large NumPy array using a for loop. Optimize it using NumPy's cumsum() function.
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12. Write a NumPy program that creates a large NumPy array and write a function to find the indices of the maximum element using a for loop. Optimize it using NumPy's argmax() function.
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13. Write a function to normalize a large NumPy array by subtracting the mean and dividing by the standard deviation using a for loop. Optimize it using vectorized operations.
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14. Write a NumPy program that generates a large 2D NumPy array and write a function to compute the column-wise mean using a for loop. Optimize it using NumPy's built-in functions.
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15. Write a NumPy program that creates a large NumPy array and write a function to sort its elements using a for loop. Optimize it using NumPy's sort() function.
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16. Write a function to calculate the outer product of two large 1D NumPy arrays using nested for loops. Optimize it using NumPy's outer() function.
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17. Write a NumPy program that creates a large 2D NumPy array and write a function to count the number of non-zero elements using a for loop. Optimize it using NumPy's count_nonzero() function.
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18. Write a NumPy program that generates a large NumPy array and write a function to compute the variance of its elements using a for loop. Optimize it using NumPy's built-in functions.
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19. Write a function to calculate the matrix product of two large 2D NumPy arrays using nested for loops. Optimize it using NumPy's matmul() function.
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20. Write a NumPy program that creates a large NumPy array and write a function to reverse its elements using a for loop. Optimize it using NumPy's slicing operations.
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