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NumPy undoubtedly offers
extremely fast, and
optimized operations.
Yet, it DOES NOT support parallelism.
This provides further scope for run-time improvement.
Numexpr is a fast evaluator for NumPy expression, which uses:
multi-threading
just-in-time compilation
The speedup offered by Numexpr is evident from the image above.
Depending upon the complexity of the expression, the speed-ups can range from 0.95x and 20x.
Read more: Documentation.
π Over to you: What are some other ways to speedup NumPy computation?
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Find the code for my tips here:Β GitHub.
I like to explore, experiment and write about data science concepts and tools. You can read my articles on Medium. Also, you can connect with me on LinkedIn and Twitter.