Links

Table of contents

Papers

PhD - Statistical learning for selectivity estimation in relational databases (manuscript, slides)
Selectivity correction with online machine learning - BDA 2020
Selectivity Estimation with Attribute Value Dependencies using Linked Bayesian Networks - TLDKS 2020
An Approach Based on Bayesian Networks for Query Selectivity Estimation - DASFAA, 2019
Entropic Variable Projection for Explainability and Intepretability - 2018
Master 2 year internship at HelloFresh (report, slides)
Master 1 year internship at Privateaser (report, slides)
Undergraduate internship at INSA Toulouse (report, slides)
Detailed solutions to the first 30 Project Euler problems

Talks

This is a list of blogs I regularly scroll through.

Tim Salimans on Data Analysis
Randal Olson
Sam & Max – French and NSFW!
Sebastian Raschka
Clean Coder
Pythonic Perambulations
Erik Bernhardsson
otoro
Terra Incognita
Real Python
Airbnb Engineering
No Free Hunch
The Unofficial Google Data Science Blog
will wolf
Edwin Chen
Use the index, Luke!
Jack Preston
Agustinus Kristiadi
DataGenetics
Katherine Bailey
Netflix Research
inFERENce
Hyndsight – Rob Hyndman is a time series specialist.
While My MCMC Gently Samples
Ines Montani – by one of the founders of spaCy.
Stephen Smerity
Peter Norvig
IT Best Kept Secret Is Optimization – by Jean-Francois Puget, aka CPMP.
explained.ai
Better Explained
Genetic Argonaut
pandas blog
Towards Data Science
Linear Digressions – data science podcasts.
Not so standard deviations – more podcasts.
Talking Machines – even more podcasts.
Practical AI – here be podcasts.
Probably Overthinking It
Simply Statistics
Practically Predictable
koaning – by Vincent Warmerdam, who made calmcode.
blogarithms
Possibly Wrong
FastML
Parameter-free Learning and Optimization Algorithms
Todd W. Schneider – this guy is really good at exploratory data analysis.
Yann Thaddée – not directly related to data science but interesting nonetheless.
Colins Blog
Fabien Sanglard – nothing to do with data science, but such good taste!
The Glowing Python – by the creator of MiniSom, which is worth checking out too.
Matt Hancock
Francis Bach – someone with an h-index of 80+ who takes the time to blog is worth reading.
Gwern Branwen – Cool in a weird way.
Libres pensées d’un mathématicien ordinaire
Count Bayesie
Jim Savage
Nick Higham – a lot of well explained algebra.
Calmcode – not a blog per se, but a nice collection of short to the point tutorials about various tools.
Chris Said
Evan Miller
Eric Jang
Andrey Akinshin
Single Lunch
Freakonometrics
Martin Daniel
Chris Kiehl
ithaka.im – a guy I met who travelled for 6 years with his wife on a bike, very inspiring.
Muthukrishnan – has written some neat document processing stuff.
Björn Ottosson
Guilherme Duarte Marmerola
Cal Paterson
Claire Carroll
Luke Metz – Luke is working on the niche topic of meta-learning at Google. He also happens a very kind person.
Practical Recommendations – a blog about recommender systems.
Robin Linacre – some good stuff related to record linkage.
Neal Lathia – machine learning in production stuff.
John D. Cook
Brandon Roberts
Allen Downey
Christophe Blefari
Scott Rome
Eugene Yan
Lj Miranda
death and gravity – great advanced Python resource.

Hall of fame

The following is a hall of fame of papers, books, and blog posts that left me with a strong impression, both in terms of content and quality.

The Elements of Statistical Learning - Jerome H. Friedman, Robert Tibshirani, and Trevor Hastie
Machine Learning - Tom Mitchell – I think this wonderful textbook is under-appreciated.
Artificial Intelligence: A Modern Approach - Russel & Norvig
mlcourse.ai – Of all the introductions to machine learning, I think this is the one that strikes the best balance between theory and practice.
Machine learning cheat sheets - Shervine Amidi
Kalman and Bayesian Filters in Python - Roger Labbe – Kalman filters are notoriously hard to grok, this tutorial nicely builds up the steps to understanding them.
CS231n Convolutional Neural Networks for Visual Recognition - Stanford
Algorithmes d’optimisation non-linéaire sans contrainte (French) - Michel Bergmann
Graphical Models in a Nutshell - Koller et al.
Rules of Machine Learning: Best Practices for ML Engineering - Martin Zinkevich – You should read this once a year.
A Few Useful Things to Know about Machine Learning - Pedro Domingos – This short paper summarizes basic truths in machine learning.
Choose Boring Technology - Dan McKinley
How to Write a Spelling Corrector - Peter Norvig – Magic in 36 lines of code.
MCMC sampling for dummies - Thomas Wiecki
Your Easy Guide to Latent Dirichlet Allocation
An Intuitive Explanation of Convolutional Neural Networks - Ujjwal Karn
An overview of gradient descent optimization algorithms - Sebastian Ruder
How to explain gradient boosting - Terence Parr and Jeremy Howard – A very good introduction to vanilla gradient boosting with step by step examples.
Why Does XGBoost Win “Every” Machine Learning Competition? - Didrik Nielsen – This Master’s thesis goes into some of the details of XGBoost without being too bloated.
Good sleep, good learning, good life - Piotr Wozniak – Extremely long and nothing to do with data science, but a very thorough essay nonetheless on how to properly sleep.
Make for data scientists - Paul Butler – I believe Makefiles are yet to be rediscovered for managing data science pipelines.
Statistical tests, P values, confidence intervals, and power: a guide to misinterpretations – Just read it.
The Cramér-Rao Lower Bound on Variance: Adam and Eve’s “Uncertainty Principle” - Michael Powers
Kaggle contest on Observing Dark World - Cam Davidson-Pilon – If you’re not convinced about the power of Bayesian machine learning then read this and get your mind blown.
A Concrete Introduction to Probability (using Python) - Peter Norvig – Extremely elegant Python coding.
The Hungarian Maximum Likelihood Trick - Louis Abraham
Machine Learning for Signal Processing - University of Illinois
Don’t Call Yourself A Programmer, And Other Career Advice
Tidy Data - Hadley Wickham – If you like playing with data then you need to be aware of this one.
Gaussian Process, not quite for dummies - Yuge Shi – Gaussian processes are quite difficult to understand (at least, for me) but Yuge gives some great visual intuitions.
Continuous Delivery for Machine Learning - Martin Fowler
Memos - Sriram Krishnan
Frequentism and Bayesianism: A Python-driven Primer - Jake VanderPlas
A Few Useful Things To Know About Machine Learning - Pedro Domingos
Multiworld Testing Decision Service: A System for Experimentation, Learning, And Decision-Making
Machine Learning: The High-Interest Credit Card of Technical Debt - Google
Variational Inference: A Review for Statisticians - David Blei and his flock
The Performance of Decision Tree Evaluation Strategies - Andrew Tulloch
Hidden Technical Debt in Machine Learning Systems - Google
Distill: Why do we need Flask, Celery, and Redis? (with McDonalds in Between) - Lj Miranda – A good example of the difference between abstract ideas and implementation details.
Darts, Dice, and Coins: Sampling from a Discrete Distribution - Keith Schwarz
Simplifying Graph Convolutional Networks - Felix Wu et al. – A nice example of putting the horse before the cart.
MIT 6.867 machine learning course notes - Tommi Jaakola – For people who enjoy concise mathematical notation.
A Recipe for Training Neural Networks - Andrej Karpathy
The Bitter Lesson - Richard Sutton
The Best Medium-Hard Data Analyst SQL Interview Questions – There are some great interactive SQL tutorials out there, such as SQLBolt and Select Star SQL, but this one takes the cake due to its complexity.
Rules of Programming - Rob Pike
Transformers from scratch - Peter Bloem
Understanding Matrix capsules with EM Routing - Jonathan Hui
A Machine Learning Primer - Mihail Eric – A good read for beginners in machine learning algorithms.
Fitting Bayesian structural time series with the bsts R package - Steven L. Scott
Novelist Cormac McCarthy’s tips on how to write a great science paper - Savage and Yeh
Emerging Architectures for Modern Data Infrastructure
What your data team is using: the analytics stack - Technically – Another solid article to understand what an analytics stack looks like in 2021.
Fred’s ImageMagick Scripts
Unprojecting text with ellipses - Matt Zucker – See also this article on page dewarping by the same author.
The Log: What every software engineer should know about real-time data’s unifying abstraction - Jay Kreps
Language models, classification and dbacl - Laird A. Breyer – machine learning on text with a UNIX philosophy.
Cameras and Lenses - Bartosz Ciechanowski – 100% worth a read.
Ditherpunk - Surma
Command-line Tools can be 235x Faster than your Hadoop Cluster - Adam Drake
Teaching An Old Dog A New Trick - Chris Kamphuis
Git scraping, the five minute lightning talk - Simon Willison – I wish I had thought about this first!
Optimal Peanut Butter and Banana Sandwiches - Ethan Rosenthal
The Data Science Hierarchy of Needs - Monica Rogati
Are Pop Lyrics Getting More Repetitive? - Colin Morris
Tuesday Changes Everything - Jesper Juul
Gently down the stream - Mitch Seymour
Les études statistiques sont-elles hors de contrôle? - David Louapre
Visually stunning math concepts which are easy to explain - StackExchange
Introduction to Locality-Sensitive Hashing - Tyler Neylon
Transformers from scratch - Peter Bloem
How to Build an Economic Model in Your Spare Time - Hal R. Varian – The academic wisdom in this article goes beyond the world of economics.
My Writings - Leslie Lamport
Modeling marketing attribution - Claire Carroll – I worked on this problem for a short time at Alan. I definitely would have done a better job if I had read this article first.
Doing Named Entity Recognition? Don’t optimize for F1 - Christopher Manning – A rather niche topic, but well explained.
Why the super rich are inevitable - The Pudding – Really cool dataviz.
Visual design rules you can safely follow every time - Anthony Hobday – good follow-up to Web Design in 4 minutes by Jeremy Thomas

Inspiring data analysis

Data sources

Eye candy

Tyler Hobbs – The god of generative arts.
Some Jean Giraud stuff
Mauro Martins
A new way to knit by Petros Vrellis
A fascinating article about Manolo Gamboa Naon
Some Ukiyo-e
Turtletoy
Dwitter
generated.space
Pixel art by Marcus Blättermann
Nick Barnes’ football bible
Simon Stålenhag
Syd Mead (who worked on Blade Runner)
Michael Fogleman’s blog
World of Warcraft art by Dreamwalker
Hors-sol de AKOREACRO
Erica Anderson
Jack Sharp
Archillect – An AI that curates cool pictures, how awesome is that?
Martin Kleppe
Zoomquilt
lossfunctions.tumblr.com – Yes, that’s a thing.
Shirts of Peter Norvig
United Airlines ads by Cream Electric Art
Miniature Calendar by Tatsuya Tanaka – Broccolis that look like trees, staples that look like workout benches… I love it!
sandspiel
Jorge Jacinto
WaveFunctionCollapse
Owen D. Pomery
einsteigenbitte.eu – I love “weird” websites like Claire Glanois'
19th Century French Artists Predicted The World Of The Future In This Series Of Postcards
Blog maps
Decktwo
eycndy.com

Cool

WindowSwap
Radio Garden
Every Noise at Once
Starlink Satellites Tracker
Based Cooking
ReadComicOnline – I recommend these French comics.
Looria – especially for cycling and camping gear
Same Energy
BOOOOOOM
indieblog.page
Cloudhiker