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Want to get better performance with Python? Here's how to use NumPy to toe the 'invisible line' of data and memory transfers and optimize efficiency.
Give your Python applications a rocket boost—here's everything you need to know to get started with Cython and its Python-to-C compiler.
Python is perfectly capable for programmers with certain tasks in math and science fields, despite perceived Python performance issues vs. other languages.
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How-To Geek on MSNRegression in Python: How to Find Relationships in Your Data
The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...
Learn about some of the best Python libraries for programming Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL).
[Zoltán] sends in his very interesting implementation of a NumPy-like library for micropython called ulab. He had a project in MicroPython that needed a very fast FFT on a micro controller, and ...
NumPy, the Python package for scientific computing, is an adolescent with prospects for a prolific maturity.
Unlike R, Python has no clear “winning” IDE. We recommend Spyder because it is well-designed for scientific computing and the popular packages associated with this type of work (NumPy, SciPy, pandas, ...
Scikits are Python-based scientific toolboxes built around SciPy, the Python library for scientific computing. Scikit-learn is an open source project focused on machine learning: classification ...
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