Maximizing Python Speed with Numpy: Vectorizing and Broadcasting (Part 3)
In the previous video, we got the our benchmark to 4 seconds. Today, we will show you how to get to 2 seconds.
We will also show you how Sean tried to improve from 2 seconds using a numpy technique—broadcasting the numpy arrays.
We started from 6 minutes and 30 seconds and ended with 2 seconds, a 200 times speed up.
Can you write even faster Python code to beat Sean's benchmark? Leave a comment below and let us know!
0:32 Full vectorized code
2:48 What is broadcasting?
Previous video in the series:
Maximizing Python Speed with Numpy Vectorization (Part 1)
• Maximizing Python Speed with Numpy Vectori...
Maximizing Python Speed with Numpy: Complexity (Part 2)
• Maximizing Python Speed with Numpy: Comple...
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