Rebuilding My Blog with Vibe Coding: Experiment and Reflections
I spent a weekend rebuilding my Jekyll blog using Claude Code and vibe coding. The result? A functional website in days instead of months. But...
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Explore all articles about data science, machine learning, and AI
Why 95% of AI Projects 'Fail' — and How to Fix It
Debunking the AI failure myth by analyzing the MIT report, discussing ROI measurement, integration challenges, and what really makes data systems succeed.
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My Databricks Handbook
After years of building in-house ML platforms, we migrated to Databricks in December 2024. This handbook shares practical tips and tricks for working with the...
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Parsing HTML with LLMs: An Arthurian Quest
Building a French TV show dataset using LLMs for HTML parsing, comparing zero-shot and few-shot prompting, and exploring fine-tuning for data extraction.
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My Decade's Journey in Data and AI
Reflections on a decade in data science and AI, covering technology trends, organizational changes, project management, and lessons learned across industries.
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Back from Recsys 2024
Key highlights from RecSys 2024 including advances in matrix factorization, LLM integration, and the latest research from Netflix, Spotify, and GroupLens.
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How Matrix Factorization Transforms User Feedbacks
A comprehensive overview of matrix factorization techniques for recommender systems, from SVD to deep learning approaches, with practical implementation tips.
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Let's Train a Suika Game Master: Crafting the Playground
Building a machine learning playground for the Suika Game using physics simulation, creating baseline agents, and setting up an experiment framework.
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Features and Design Principles of a Recommender System
A comprehensive guide to designing recommender systems in 2024, covering core features, design principles, and practical implementation strategies.
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Meetup Milestone: Navigating my First Year as an Organizer
So it's been 1 year now since I started to get involved in organizing two meetup groups in MTL with Pydata MTL and MLOps Community...
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Exploring French podcast transcription with OpenAI Whisper
Experimenting with OpenAI's Whisper to transcribe French podcasts, comparing different deployment strategies, and benchmarking costs and performance.
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Data scientist & Machine learning engineer: Decoding the roles
Exploring the roles of data scientists and machine learning engineers, their differences, and how they complement each other in modern ML projects.
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Back from Apply(ops) 23 conference
Key takeaways from Apply(ops) 23 conference featuring insights from Uber, Lidl, Hello Fresh, and Pinterest on MLOps platforms, multi-cloud strategies, and production ML at scale....
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Back from Recsys 2023
Comprehensive recap of RecSys 2023 covering industry practices, reproducibility research, new datasets, transformers in recommendations, and practical insights from Netflix, BBC, and Pinterest.
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Fallbacks and Serving Rules - The Underestimated Pillars of Recommender System Success
Explore fallback strategies and serving rules in recommender systems. Learn how these underestimated pillars ensure reliable predictions in production environments.
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Five years in the making, my MLOps journey in the video game industry
Five years of MLOps journey at Ubisoft building ML platforms for video games. Insights on challenges, tools, workflows, and lessons learned bringing ML to production....
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Cold Start No More: Using transformers to build decks in Marvel Snap
Tackle the cold start problem in recommender systems using transformers. Build a Marvel Snap deck recommendation system handling new cards with embedding techniques.
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Bringing Machine Learning to Production at Ubisoft (PydataMTL June22)
Explore bringing machine learning from R&D to production at Ubisoft. Learn about creating an ML platform to support data scientists building production-ready pipelines.
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Navigating Unity as an ML Practitioner: A Personal Journey
The following article will focus on my first experiences as an ML practitioner in Unity, a popular game engine. First, we'll start by introducing game...
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Back from Recsys 2022
Hello, this is autumn and who says autumn says Recsys time, and this year Seattle was the place to be. I attended digitally to the...
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Deploy your data pipeline with Docker and AWS ECS
I recently decided to experiment with Docker containers to build standalone applications to optimize the operation flow of my different data/scraper pipelines. I have limited...
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Design and version your ML workflow with DVC (Kaggle competition)
For a few months, I wanted to test DVC, a toolkit around versioning for ML projects built by iterative. I tried it a bit at...
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Collaborative filtering and two stage recommender system with Surprise
Explore Surprise, a Python scikit package for building recommender systems on explicit ratings. Learn collaborative filtering and two-stage recommender implementations.
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Start your time-serie project (analysis, forecast and anomaly detection) with Kats
Recently I heard about a package developed by Facebook research (META research !?) called KATS, released by Facebook's Infrastructure Data Science team end of last...
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Deploy a pipeline to collect data on Twitter and Google trends
Hello, in this article, I will give you a quick tour of a project that I recently resurrected from the dead to collect the French...
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Build a ventilator pressure predictor for Google Brain
I wanted for a long time to participate thoughtfully in a Kaggle competition ( I think I made some tests a few years ago but...
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Takeaways from RecSys 2021
Once again, I attended (virtually) this year with some of my colleagues at RecSys 2021 in Amsterdam. In this article, I will recap exciting papers...
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Build an image classifier with fastai
I recently started to prototype an image classifier at work, and this work led me to the fastai package that I had in my backload...
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Evaluation of recommender systems (metrics and baseline models)
I focused on this topic for the past three years at Ubisoft, but I never found suitable datasets to use for experiments on my blog...
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Tune your machine learning workflow with weights and biases, mljar automl, hyperopt, shapash and evidently
I wanted to write for a few weeks around ml/ds libraries that I have on my backlog of things to try. One article per library...
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Kickstart a big data project with AWS EMR and Pyspark
Hello readers, I wanted a long time to write an article on an AWS service that I am using in my daily job called EMR....
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Feedback and discoveries on RecSys 2020
In this article, there will be a description on the Recsys conference that happened in September 2020 virtually (Thanks Ubisoft to have offer me the...
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Be more productive and self-sufficient to produce ML applications with AWS Sagemaker
In this article, there will be an overview of the service of AWS Sagemaker. The idea will be to see from my DS perspective how...
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Time-series forecasting and causal analysis in R with Facebook Prophet and Google CausalImpact
This article will be part of my annual dive in R; the idea will be to use two R libraries in time-series forecasting and causal...
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Initiation to graph database with neo4j and Beat Saber
In this article, there will be an introduction to the Neo4j graph database, leverage the technology for analytics and recommendation purposes.
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Introduction of TensorFlow 2.0
In this article, I am going to present some of my findings on my exploration of TensorFlow, the idea will be with TensorFlow to build...
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Music information retrieval with LibROSA and Beat Saber
In this article, I am going to illustrate some of the works around music information that I work since the past few weeks applicated to...
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Be more efficient to produce machine learning pipeline with Metaflow
For this article, I am going to describe my hands-on on a new library that has open-sourced recently by Netflix to operate and version machine...
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How to build a dataset for an image classifier from scratch (related to cars)
In this article, I am going to present a pipeline that I built a few weeks ago to collect data (text and pictures) from the...
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Dive in HearthStone from a data perspective
Hello, in this article, I am going to detail a dataset that I built a few weeks ago on the game Hearthstone.
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Be more effective to produce machine learning models with mlflow
The version used for this article is mlflow 1.4.0
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Crossfit Games - Retrospective of the Open 2019
Hello, the season of the Open starts again this year (once again !?) so I am writing this article to:
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PUBG - Make analytics with AWS and plotly
For this article, I am going to start the analysis of the data extracted with the pipeline explained on this article. The goal of this...
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Analysis of the energy performance certificates with Dataiku DSS
Since I published the article on the London smart meter and the possible analysis of the data, I am receiving regularly messages of people that...
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Build a data pipeline on AWS
I started this project in echo of the Kaggle competition related to PUBG, where the goal was to predict the player rank in the match,...
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Scraping and analysis of the Crossfit Opens data
Learn how to build a web scraping system to collect and analyze Crossfit Open data, including athlete profiles, gym information, and performance metrics from the...
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Building a dashboard with Dash (plotly), AWS and Heroku
Learn how to build an interactive dashboard using Dash (Plotly) to visualize personal fitness and health data from Nokia devices, Strava, and Crossfit sessions.
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Analysis of smart meter data in London (UK)
Hello, the goal of this article is to offer a clear description of the dataset that I uploaded in November 2017 on Kaggle followed by...
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Make a forecast system of the French national energy consumption
Hello readers, for this article I am going to explain my approach to create a forecast system of the French (metropolitan) energy consumption. This kind...
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How to deploy a Messenger bot in Python
Hello reader, in this article I will explain my approach to deploy a chatbot in Python on the Messenger platform.
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Hello World
Welcome to my blog where I share projects and insights from my work as a data scientist at EDF Energy in England, with a focus...
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