Data Science and Machine Learning (Theory and Projects) A to Z - NumPy for Numerical Data Processing: Slicing-Part 2

The video tutorial covers various operations on arrays using Numpy. It starts with locating elements in arrays and finding their indices. It then explores two-dimensional array operations, including accessing specific elements, rows, and columns. The tutorial also introduces Numpy's linear algebra library, highlighting functions like eigenvalues and matrix inversion. Finally, it discusses sorting arrays by rows and columns, emphasizing the use of axes for sorting multidimensional arrays.

Which function can be used to find the index of an element in an array?

• np.locate

• np.search

• np.find

• np.where

How can you scale and round the values of a 2D array generated with random values between 0 and 1?

• Multiply by 10 and use np.round

• Add 10 and use np.ceil

• Multiply by 100 and use np.floor

• Divide by 10 and use np.round

What is the index of the second row and third column in a 2D array?

• (2, 3)

• (1, 2)

• (0, 1)

• (3, 2)

Which function is used to transpose a matrix in Numpy?

• np.reverse

• np.flip

• np.swap

• np.transpose

What does the LA.inverse function in Numpy do?

• Finds the inverse of a matrix

• Computes the eigenvalues of a matrix

• Performs matrix multiplication

• Calculates the determinant of a matrix

How can you sort each column of a 2D array individually?

• Use sort with axis=1

• Use sort with axis=0

• Use sort with axis=2

• Use sort with axis=-1

What is the next topic to be covered after sorting arrays?

• Matrix multiplication

• Statistical analysis

• Fancy indexing or masking

• Data visualization