# 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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