15Nov/18

# Meetup Machine Learning Aix-Marseille S04E02

Tonight I am participating in the Machine Learning Aix-Marseille Meetup, for the second session of this fourth edition. I am speaking after Leonardo Noleto, senior data scientist at Bleckwen FinTech who is developing a solution to fight financial fraud with machine learning. I will present the project on which Enora Belz, Romain Gaté, Vincent Malardé, Jimmy Merlet, Arthur Charpentier and I worked on last summer for the 2018 Football World Cup (see a previous post). The idea was to use machine learning techniques to predict the outcome of football matches (win, draw or defeat).

The slides are available here (in French): http://www.egallic.fr/Recherche/Worldcup_2018/2018_meetup_ML/egallic_meetup.html

06Jun/18

# Coupe du Monde 2018: Paul the octopus is back

On the occasion of Euro 2008 and Mondial 2010, the Oberhausen oracle (more commonly known as “Paul the octopus”) made the headlines. His exact predictions regarding the results of the German team at Euro 2008 and the appointment of the winning team of the 2010 World Cup (Spain) are still etched in the memories. With some colleagues (Enora Belz, Romain Gaté, Vincent Malardé and Jimmy Merlet) we tried to continue the work of the late Paul the octopus to predict the outcome of the upcoming meetings of the 2018 World Cup. To do this, we rely on the results of past World Cup and Continental Cup meetings.1

17Nov/16

# Where’s Waldo? Here he is!

Yesterday, I came across a nice article untitled “Here’s Waldo: Computing the optimal search strategy for finding Waldo“, written by Randal S. Olson. I used the data he shared to apply a correction to the kernel density estimation of Waldo’s location.

In this article, Randal explains that he has devoted some time to try to compute the optimal search strategy for finding Waldo. To that end, he has used some machine learning techniques.
From an image provided by Slate (Here’s Waldo, 2013, by Ben Blatt), Randal S. Olson retrieved the coordinates of 68 different locations of Waldo, and kindly shared the data afterwards.

[…]

18Jan/16

# Maps with R: slides

The other day, someone asked me if it was easy to do maps with R. My first thought was: “of course, it is”. I offered to prepare a few slides. I guess it was not that simple after all because one actually needs quite a lot of basic knowledge to be able to create its own map.

03Nov/14

# French dates in R – From Mac OS to Windows

The other day during my R lecture, something I did not expect happen… I should have known, or at least guess that it would not work… But I wanted to believe it would. When I gave examples on how to read both English and French formatted dates in R, what was working perfectly on Mac OS X did not on Windows Seven. The example was the following:

d_char_fr <- "Mer 04 Fév 2015"
d_char <- "Wed 04 Feb 2015"
as.Date(d_char_fr, format = c("%a %d %b %Y"))
as.Date(d_char, format = c("%a %d %b %Y"))

30Oct/14

# Coordinates of “hot-spots”

Last week I uploaded a note about the paper @freakonometrics and I have submitted again after we added quite a few revisions. We have already made available most of the R code to reproduce our applications (on this GitHub repository). However, we did not share our method to obtain the coordinates of the “hot-spots” areas

22Oct/14

# Kernel Density Estimation with Ripley’s Circumferential Correction

This is it! The revised version of a paper written with Arthur Charpentier has been submitted yesterday! It is untitled “Kernel Density Estimation with Ripley’s Circumferential Correction”. The paper is available on https://hal.archives-ouvertes.fr/hal-00725090.

19Apr/14

# Maps with R

Last month, @freakonometrics posted a bunch of articles on his blog about the North pole (in French):

There are some maps on these articles that were produced using ggplot2 excellent package in R. We want to share our code here.

03Jan/14

# Tweet goes viral

To begin this new year, I had the pleasure to have some fun with R, Gephi and Twitter.