Asked on Twitter why a paper is coming out now, 15 years after NumPy's creation, Stefan van der Walt of the University of California at Berkeley's Institute for Data Science, one of the article's ...

As with statsmodels, Matplotlib does have a learning curve. There are two major interfaces, a low-level "axes" method and a ...

Python is convenient and flexible, yet notably slower than other languages for raw computational speed. The Python ecosystem has compensated with tools that make crunching numbers at scale in Python ...

[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 was ...

Overview: NumPy is ideal for data analysis, scientific computing, and basic ML tasks.PyTorch excels in deep learning, GPU ...

Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...

With Python and NumPy getting lots of exposure lately, I'll show how to use those tools to build a simple feed-forward neural network. Over the past few months, the use of the Python programming ...

If the mention of algebra conjures bad memories of math classes, a Python library called SymPy could change your mind about ...

Although neural networks have been studied for decades, over the past couple of years there have been many small but significant changes in the default techniques used. For example, ReLU (rectified ...