My latest contribution for scikit-learn is
an implementation of the isotonic regression model that I coded with
Nelle Varoquaux and
Alexandre Gramfort …

Householder matrices are square matrices of the form

$$ P = I - \beta v v^T$$

where $\beta$ is a scalar and $v$ is …

** Note: this post contains a fair amount of LaTeX, if you don't
visualize the math correctly come to its original location **

In …

Besides performing a line-by-line analysis of memory consumption,
`memory_profiler`

exposes some functions that allow to retrieve the memory consumption
of a function in real-time, allowing e.g. to visualize the memory
consumption of a given function over time.

The function to be used is `memory_usage`

. The first argument
specifies what …

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 …

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 …