About this tech blog
💬 " I created this tech blog to share my
💡
knowledge
and experiences with you, around
all the challenges
that I have encountered, then resolved or tried to overcome about
computer science,
data science, and
applied mathematics
.
In addition to writing content, I developed this blog as an
open-source
project
🧪Jekyll Tech Blog
for the
open internet
,
you can either re-use it as a template for your blog or contribute to it.
The
external resources
of the published blog posts like code, slides, diagrams, images or references are available.
Also, I write content on
Medium
. ”
About the community
Writers
Co-write content or create your blog
Contributors
Contribute to the open-source project
About open source and freemium tools used
Here are open source and freemium used to build this tech blog based on the framework 🧪 Jekyll Tech Blog , that I developed:
About me
💬 " Currently, I am based in 
Paris. I work as Staff Software Engineer in the 
Criteo AI Lab, inaugurated in 2018, in the first 🦄 french unicorn: Criteo. This company contributes, since its creation in 2005, machine learning ecosystem,
in the sector of the ad tech, with an mindset to defend a free and open internet;
mixing 
data engineering
and 
artificial intelligence challenges
at 
high scale
through 
research and development. More particularly, I am responsible since 2020 to build an enhanced and unified e-commerce catalog composed of
+30K catalogs and +25B products made with import and enrichment steps with data pipelines offline and online executing AI processors about categorization, brandization, and de-deduplication
of e-commerce products especially. This 
huge e-commerce
dataset is consolidated with transactional and behavioral consumer data, then used by 
online engines to recommend and search e-commerce products to which I also contribute,
it evolved and is evolving gradually to 
deep learning and 
large language models. These tools are available for the worldwide e-commerce market on the 3 main business areas: AMERICA, EMEA and ASIA, and are accessible via a
SaaS platform for demand and supply chains.
I explored all the different tech aspects from hardware to software through ecosystems in 
start-up and 
multinational organization
for 10+ years. I am very excited by the start-up company world from the process of creation to the evolution of a large company.
Before I worked as software reliability engineer and web full stack developer.
After advanced studies in engineering and research and these accumulated professional experiences,
I acquired soft and hard skills in
computer science,
data science, and
applied mathematics
with a specialization in information systems, machine learning, and big data.
Here my 
technical stack,
that is to say, some technologies that I have already used. It is non-exhaustive, new technologies occur and disappear over time, and the list continues to
increase, and I use only some of them in the function of the project on which I work:
I love coding algorithms or/and doing applied mathematics. I am passionate about computer science and data science, and more generally about informatics and mathematics. My favorite programming languages, among those I use, are:
Java |
Scala |
Python |
Bash.
under the 
/
GNU/Linux
operating system with the distribution 
Ubuntu
for the development
One of my preferred mathematics formulae is the Euler's identity:
$ e^{i\pi} + 1 = 0 $ .
Among my favorite informatics programs is the fork bomb:
:(){ :|:& };:
Else, I like 
rugby, 
soccer, 
magic the gathering arena, and the juggling, especially the 
“diabolo”.
Since the beginning of my educational and professional career, I followed this mindset:
I started my education in applied mathematics and statistics,
developed 🏴☠️ hacking skills, then explored the different 📊 domain expertises.
Now, I am mixing and practicing all these skills. These competencies allow browsing in each job position and role: software (hardware) engineer, machine learning engineer,
data scientist, data analyst, business intelligence engineer, data engineer, entrepreneur and researcher
required to develop a project of data science, where the 
researcher and 
software engineer plays an essential role: the first one is in advance
to the industry providing the potential applied and fundamental theory for the 
future and the second one is a 🧬 generic position
to be transverse, existing before these specializations. While data analyst, entrepreneur and business intelligence engineer are more linked 
financial aspects,
and are among the business stakeholders. "
About the logo
The logo of this blog is composed of a $\rhd$ buffer logic gate and a $\Sigma$ uppercase sigma to represent respectively
the strong relationships between
computer science,
data science, and
applied mathematics
:
the buffer accumulates the knowledge in the input before propagating it to the sigma to generate a synthesized output.
