SciPy contains two methods to compute the singular value decomposition (SVD) of a matrix: scipy.linalg.svd and scipy.sparse.linalg.svds. In this post I'll compare both methods for the task of computing the full SVD of a large dense matrix.

The first method, scipy.linalg.svd, is perhaps …

This tutorial introduces the concept of pairwise preference used in most ranking problems. I'll use scikit-learn and for learning and matplotlib for …

My newest project is a Python library for monitoring memory consumption of arbitrary process, and one of its most useful features is the line-by-line analysis of memory usage for Python code. I wrote a basic prototype six months ago after being surprised by the lack of related tools. I wanted …

A little experiment to see what low rank approximation looks like. These are the best rank-k approximations (in the Frobenius norm) to the a natural image for increasing values of k and an original image of rank 512.

Python code can be found here. GIF animation made using ImageMagic's convert …

In scipy's development version there's a new function closely related to the QR-decomposition of a matrix and to the least-squares solution of a linear system. What this function does is to compute the QR-decomposition of a matrix and then multiply the resulting orthogonal factor by another arbitrary matrix. In pseudocode …

Last week we released a new version of scikit-learn. The Changelog is particularly impressive, yet personally this release is important for other reasons. This will probably be my last release as a paid engineer. I'm starting a PhD next month, and although I plan to continue contributing to the project …

I've been working lately in improving the scikit-learn example gallery to show also a small thumbnail of the plotted result. Here is what the gallery looks like now:

And the real thing should be already displayed in the development-documentation. The next thing is to add a static image to those …

Today's coding sprint was a bit more crowded, with some notable scipy hackers such as Ralph Gommers, Stefan van der Walt, David Cournapeau or Fernando Perez from Ipython joining in. On what got done: - We merged Jake's new BallTree code. This is a pure Cython implementation of a nearest-neighbor …

As a warm-up for the upcoming EuroScipy-conference, some of the scikit-learn developers decided to gather and work together for a couple of days. Today was the first day and there was only a handfull of us, as the real kickoff is expected tomorrow. Some interesting coding happened, although most of …

Ridge coefficients for multiple values of the regularization parameter can be elegantly computed by updating the thin SVD decomposition of the design matrix:

import numpy as np
from scipy import linalg
def ridge(A, b, alphas):
    """
    Return coefficients for regularized least squares

         min ||A x - b||^2 + alpha ||x||^2 …