# 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 …

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

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.

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

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

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

The *logistic ordinal regression* model …

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 …