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PyData Paris - April 2015

Last Friday was PyData Paris, in words of the organizers, ''a gathering of users and developers of data analysis tools in Python''.

The organizers did a great job in putting together and the event started already with a full room for Gael's keynote

Gael's keynote

My take-away message from the talks is …

Data-driven hemodynamic response function estimation

My latest research paper[1] deals with the estimation of the hemodynamic response function (HRF) from fMRI data.

This is an important topic since the knowledge of a hemodynamic response function is what makes it possible to extract the brain activation maps that are used in most of the impressive …

Plot memory usage as a function of time

:og_image: http://fa.bianp.net/blog/images/2014/mprof_example.png

One of the lesser known features of the memory_profiler package is its ability to plot memory consumption as a function of time. This was implemented by my friend Philippe Gervais, previously a colleague at INRIA and now at Google.

With …

Surrogate Loss Functions in Machine Learning

TL; DR These are some notes on calibration of surrogate loss functions in the context of machine learning. But mostly it is …

Different ways to get memory consumption or lessons learned from ``memory_profiler``

As part of the development of memory_profiler I've tried several ways to get memory usage of a program from within Python. In this post I'll describe the different alternatives I've tested.

The psutil library

psutil is a python library that provides an interface for retrieving information on running processes. It …

Numerical optimizers for Logistic Regression

In this post I compar several implementations of Logistic Regression. The task was to implement a Logistic Regression model using standard optimization …

Logistic Ordinal Regression

TL;DR: I've implemented a logistic ordinal regression or proportional odds model. Here is the Python code

The logistic ordinal regression model …

Isotonic Regression

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

Householder matrices are square matrices of the form

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

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

Loss Functions for Ordinal regression

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

In …