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...
MUSIC
Nimbus by Eveningland
https://www.youtube.com/audiolibrary/...
On this page of the site you can watch the video online Maximizing Python Speed with Numpy: Vectorizing and Broadcasting (Part 3) with a duration of hours minute second in good quality, which was uploaded by the user Software for Science 14 March 2019, share the link with friends and acquaintances, this video has already been watched 624 times on youtube and it was liked by 15 viewers. Enjoy your viewing!
