About this blog

Gilles Legoux
Staff Software Engineer
GitHub LinkedIn Stack Overflow Medium

“ 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 computer science, data-science data science, and applied-mathematics applied mathematics . In addition to writing content, I developed this blog as an open source project open source project:🧪Jekyll Tech Blog for the open internet open internet, you can either re-use it as a template for your blog or contribute to it. The :newspaper: external resources of the published blog posts like code, slides, diagrams, images or references are available. Also, I write content on Medium Medium . ”

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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:

Open source and Freemium tools
Open source and Freemium tools [built by author]

About me

Currently, I am based in eiffel-tower Paris. I work as Staff Software Engineer in the criteo-ai-lab 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 open-internet free and open internet; mixing data data engineering and artificial-intelligence artificial intelligence challenges at high-scale high scale for research-development 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 through 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 dataset huge e-commerce dataset is consolidated with transactional and behavioral consumer data, then used by ai-engineonline engines to recommend and search e-commerce products to which I also contribute, it evolved and is evolving gradually to deep-learning deep learning and llm 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 startup start-up and multinational-company 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 computer science, data-science data science, and applied-mathematics applied mathematics with a specialization in information systems, machine learning, and big data.

Here my stack 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 Java | scala Scala | python Python | bash Bash.

under the GNU/linux GNU/Linux operating system with the distribution ubuntu Ubuntu for the development

One of my preferred formulae is the Euler's identity:

$ e^{i\pi} + 1 = 0 $ .

Else, I like :rugby_football: rugby, :soccer: soccer, mtga magic the gathering arena, and the juggling, especially the diabolo “diabolo”.

Since the beginning of my educational and professional career, I followed this mindset:

Venn diagram to master computer science, data science and applied mathematics
Venn diagram to master computer science, data science and applied mathematics [adapted from source]

I started my education in applied-mathematics 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 :clipboard: researcher and :computer: software engineer plays an essential role: the first one is in advance to the industry providing the potential applied and fundamental theory for the :rocket: 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 :dollar: financial aspects, and are among the business stakeholders.

AI processor with machine learning lifecycle
AI processor with machine learning lifecycle [adapted from source]

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 computer science, data-science data science, and applied-mathematics applied mathematics : the buffer accumulates the knowledge in the input before propagating it to the sigma to generate a synthesized output.