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SUMMARY:Using Cython and C++ kernels to speed up Python libraries - Anatol
 y Volkov\, David Cortes
DTSTART;TZID=Europe/Warsaw:20250819T103000
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DTSTAMP:20260907T115747Z
UID:pretalx-euroscipy-2025-D78ZJP@pretalx.com
DESCRIPTION:Many high-performance Python frameworks\, such as NumPy\, scik
 it-learn\, and PyTorch\, rely on primitives implemented in Cython and C++ 
 to achieve optimal performance.  \n\nIn this tutorial\, we will explore ho
 w to implement custom kernels in Cython and C++ and integrate them into Py
 thon projects. Using Linear Regression model trained with Normal Equations
  method as an example\, we will demonstrate how to accelerate numerical co
 mputations by writing efficient kernels in Cython and C++. We will also di
 scuss when implementing custom kernels is beneficial and when existing opt
 imized libraries offer the best performance.  \n\nThis tutorial is aimed a
 t intermediate Python users. At the same time C++ knowledge is advantageou
 s but not mandatory.
LOCATION:Room 1.38 (Ground Floor)
URL:https://pretalx.com/euroscipy-2025/talk/D78ZJP/
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