- Premery (France) // Paris (France)
Stars
A micro HTTP Web server that supports WebSockets, html/python language templating and routing handlers, for MicroPython (used on Pycom modules & ESP32)
Set up a kaios app by running one command.
Select, put and delete data from JSON, TOML, YAML, XML and CSV files with a single tool. Supports conversion between formats and can be used as a Go package.
Code release for SLIP Self-supervision meets Language-Image Pre-training
🔬 A data science oriented container launcher
A sidecar app which clones a git repo and keeps it in sync with the upstream.
The flexible backend for all your projects 🐰 Turn your DB into a headless CMS, admin panels, or apps with a custom UI, instant APIs, auth & more.
⚡️ Express inspired web framework written in Go
Bot Discord proposant une interface front cohérente et pertinente avec le bot de commandes. L'objectif est d’évaluer l’ensemble des compétences travailler pendant notre parcours d’études en back-en…
🥭 | A Golang repository template with conventions, guidelines, project folder structure, Dockerization, CI/CD, labeler, releaser, automation [...] and some more, to start a new Go project in SECONDS.
County park trail map for Brown County, Wisconsin
Create and update circles in Geojson for maps and analysis
Use Mapbox GL JS to visualize data in a Python Jupyter notebook
Slice GeoJSON into vector tiles on the fly in the browser
Architecture decision record (ADR) examples for software planning, IT leadership, and template documentation
Standard Go Project Layout
Set up a modern web app by running one command.
RandomX, KawPow, CryptoNight and GhostRider unified CPU/GPU miner and RandomX benchmark
Implementation of the most important parts of the Lottery Ticket Hypothesis Paper
A repository in preparation for open-sourcing lottery ticket hypothesis code.
Implementing "The Lottery Ticket Hypothesis" paper by "Jonathan Frankle, Michael Carbin"
This repository contains a Pytorch implementation of the paper "The Lottery Ticket Hypothesis: Finding Sparse, Trainable Neural Networks" by Jonathan Frankle and Michael Carbin that can be easily a…