Julien Jerphanion 12/16/2021

Performance and scikit-learn (1/4)

Read Original

This article provides a technical overview of scikit-learn's dependencies and core performance bottlenecks. It explains how CPython's interpreter overhead, the Global Interpreter Lock (GIL), inefficient memory patterns in NumPy operations, and the absence of 'bare-metal' data structures limit computational efficiency in the PyData ecosystem.

Performance and scikit-learn (1/4)

Comments

No comments yet

Be the first to share your thoughts!

Browser Extension

Get instant access to AllDevBlogs from your browser