Question 1
What is the result of fancy indexing?
Question 2
What does the following code return: `plt.plot(x, x**2); plt.show()`?
Question 3
What does `np.linspace(-10, 10, 100)` do?
Question 4
What rule does NOT apply to broadcasting in NumPy?
Question 5
How can memory usage be optimized in NumPy?
Question 6
What is the role of the np.isnan() function?
Question 7
For the NumPy expression `a = np.array([...])`, which operation correctly illustrates boolean indexing?
Question 8
What is the formula for the sigmoid function?
Question 9
What is one reason why NumPy is faster than Python lists?
Question 10
How do you calculate the Mean Square Error (MSE) using NumPy?
Question 11
In matplotlib, which function is used to plot a linear function?
Question 12
Why is NumPy preferred for numerical operations over Python lists?
Question 13
Which of the following arrays can be broadcasted together: array A of shape (4,3) and array B of shape
Question 14
What will be the result of `a[~np.isnan(a)]` if `a = np.array([1, 2, np.nan, 4])`?
Question 15
Which of the following operations uses boolean indexing?