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Showing posts with the label Performance
Create A Matrix From A Vector Where Each Row Is A Shifted Version Of The Vector

Create A Matrix From A Vector Where Each Row Is A Shifted Version Of The Vector

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I have a numpy array like this import numpy as np ar = np.array([1, 2, 3, 4]) and I want to creat… Read more Create A Matrix From A Vector Where Each Row Is A Shifted Version Of The Vector
Python Efficient Way To Check If Very Large String Contains A Substring

Python Efficient Way To Check If Very Large String Contains A Substring

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Python is not my best language, and so I'm not all that good at finding the most efficient solu… Read more Python Efficient Way To Check If Very Large String Contains A Substring
What Is The Time Complexity Of .at And .loc In Pandas?

What Is The Time Complexity Of .at And .loc In Pandas?

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I'm looking for the time complexity of these methods as a function of the number of rows in a d… Read more What Is The Time Complexity Of .at And .loc In Pandas?
Python: Why Are * And ** Faster Than / And Sqrt()?

Python: Why Are * And ** Faster Than / And Sqrt()?

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While optimising my code I realised the following: >>> from timeit import Timer as T >&… Read more Python: Why Are * And ** Faster Than / And Sqrt()?
Fast Combinations Without Replacement For Arrays - Numpy / Python

Fast Combinations Without Replacement For Arrays - Numpy / Python

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I'm after generating efficiently pairwise combinations from 1D array(s). Itertools is just too … Read more Fast Combinations Without Replacement For Arrays - Numpy / Python
Fast Information Gain Computation

Fast Information Gain Computation

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I need to compute Information Gain scores for >100k features in >10k documents for text class… Read more Fast Information Gain Computation