How will you generate a matrix that follows Bernoulli distribution in python? Divide each element of the matrix with sum of columns.
What's the process for generating a Python matrix with Bernoulli distribution, with each element adjusted by its column's total?
Could you demonstrate how to produce a Bernoulli-distributed matrix in Python and normalize each element by column totals?
In Python, what steps would you take to instantiate a matrix adhering to the Bernoulli distribution, then adjust each entry by the sum of its column?
Can you write a Python function that yields a Bernoulli-distributed matrix and scales each element by the sum of its respective column?
What method would you use in Python to generate a matrix under a Bernoulli distribution, followed by division of each element by its column sum?
Please show how to create a Bernoulli distributed matrix in Python, with each matrix element divided by the column sum.
How to construct a matrix following a Bernoulli distribution in Python, with elements normalized by their column sums?
In Python, how do you fabricate a matrix following the Bernoulli distribution, and then normalize by each column's sum?
How do you go about creating a matrix that is Bernoulli-distributed in Python, with post-creation normalization per column sum?
How can you create a Bernoulli-distributed matrix in Python, ensuring each element is normalized by the column sum?