Discover @marciorasf Open Source projects

Márcio Andrade (@marciorasf)

marciorasf

Stars
35
Global Rank 438,984 (Top 16 %)
Followers 12
Following 5
Registered over 7 years ago
Most used languages

Python
40.9 %

TypeScript
22.7 %

JavaScript
18.2 %

Shell
9.1 %

Elixir
4.5 %

Dockerfile
4.5 %
Location 🇺🇸 United States
Country Total Rank 82,464
Country Ranking

Elixir
2,017

Dockerfile
2,856

TypeScript
8,971

local-aws

Base configurations that I use to simulate a local AWS.

b3-ranking

Project to help people getting stocks indicators at B3 and rank them.

websocket-test

Playing around with websockets.

hippocards-web

Hippocards is a tool that helps people studying with flashcards.

hippocards-api

Hippocards is a tool that helps people studying with flashcards.

b3-ranking-web

Front end for the b3-ranking project.

docker-fundamentals

This repo is a guide to learning the fundamentals of Docker.

MGraph.js

Graph structure and methods implemented in javascript.

sonic

McCulloch-Pitts-Model

Basic implementation of the McCulloch-Pitts Model

tic-tac-toe

Simple tic tac toe with some bot intelligence built with react.

marciorasf

My profile info.

artificial-neural-networks

Repository for the codes of the Artificial Neural Networks discipline.

python-template

A basic template that I use for python projects.

python-playground

This repo is where I save my Python random stuff.

picsize-test-web

Frontend of picsize admission test.

picsize-test-api

Backend of picsize admission test.

fuzzy-systems

Files used on Fuzzy Systems discipline (UFMG ENG 008).

design-patterns-python

Repo containing examples of design patterns usage in Python 3.

next-level-week-5-Elixir

This is a project named Inmana developed during NLW5 - Next Level Week 5 - Elixir offered by Rocketseat.

rudimentar-cpp-tester

This is a simple tester for c++ files that runs on terminal.

next-level-week-2-fullstack

This is a project named Proffy developed during NLW2 - Next Level Week2 offered by Rocketseat.

evolutionary-computing

Repo with the algorithms developed on the Evolutionary Computing discipline of the graduate program of the Electrical Engineering Department - UFMG.