Notebook Gallery#
API REST#
A few notebooks on REST API.
Challenges#
The following notebook introduce materials, explanation for challenge about algorithmic or data.
Guess working and living areas in a city#
Shared bicycles are available in almost every big city around the world. The data about available bicycles or trips are usually open. These notebooks show some ways to collect and use this data.
Optimize a route#
What is the shortest path going through a set of streets in a city? You will find some tips about the answer among the following notebook.
k-Nearest Neighbours and Sparse features#
This a kind of mathematical puzzle which happens in a machine learning problem. Thatt riddle shows why sometimes it is quite helpful to understand a little bit of the mathematics behind the scenes.
Trajectoires de vélib#
Le système vélib permet de connaître l’état des stations à intervalles réguliers. Ces données permettent-elles d’estimer la vitesse moyenne des cyclistes utilisant ce moyen de locomotion ? Que peut-on imaginer pour calculer un estimateur de cette vitesse ?
Cheat Sheets#
Tips, tricks, tweaks about anything.
Coding Problems#
Enigma, coding problems, exercises pour interviews…
hackathon_2015#
Materials for the ENSAE Hackathon 2018#
See more about this hackathon at Hackathon ENSAE / BRGM / Microdon / Latitudes / Genius / Ernst & Young - 2018.
hackathon_2022#
Premier pas en machine learning#
Quelques idées simples pour démarrer avec des données.
