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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the command to create a 2D NumPy array with values [[1, 2], [3, 4]]?
💡 Hint: Think about the syntax `np.array()`.
Question 2
Easy
What does np.zeros((3, 3)) do?
💡 Hint: Recall what zeros represent in initialization.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What does NumPy stand for?
- Numerical Python
- Normal Python
- Numpy Language
💡 Hint: Think about the focus of this library.
Question 2
True or False: NumPy arrays are slower than Python lists in numerical operations.
- True
- False
💡 Hint: Think about why we use NumPy in machine learning.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are given an array of shape (3, 4). Reshape it into a shape of (2, 6). How do you do it, and what does the resulting array look like?
💡 Hint: Remember, the total number of elements must stay constant.
Question 2
Implement a Python function using NumPy to normalise an array (subtract the mean and divide by the standard deviation). What will be the general structure of your function?
💡 Hint: Think about mean and std calculations, and how they relate to normalizing data.
Challenge and get performance evaluation