marianafmedeiros Goto Github PK
Name: Mariana Medeiros
Type: User
Bio: I have always liked the power and magic that come from a computer and now I am a data everything lifetime student 👩💻 I am also a coffee and gym lover ☕ 🏋️
Mariana Medeiros's Projects
alura-cafecoflix-reactjs
Netflix-like project made during the mini course promoted by Alura
app-analysis-challenge
bda_course_aalto
Bayesian Data Analysis course at Aalto
btc_data
This repository contains the code and datasets for creating the machine learning models in the research paper titled "Time-series forecasting of Bitcoin prices using high-dimensional features: a machine learning approach"
codenationds
Repository with all the activities developed during the course on Data Science
computer-science
:mortar_board: Path to a free self-taught education in Computer Science!
dataquest
Repository with all my Dataquest projects
deep-reinforcement-learning-for-automated-stock-trading-ensemble-strategy-icaif-2020
Deep Reinforcement Learning for Automated Stock Trading: An Ensemble Strategy. ICAIF 2020. Please star.
dio-api.net-mongodb-coronavirus
Projeto prático de construção de uma aplicação API em .NET para exercitar conceitos das aulas e framework MVC
donation-website
finrl
FinRL: Financial Reinforcement Learning. 🔥
gamaxp_airbnb
gamaxp_cpfvalidator
gamaxp_pokestore
A simple pokestore made with ReactJS and Bootstrap as an activity for GamaXP bootcamp.
gamaxp_sitecovid
kafka-exercise
An exercise running Kafka, Kafka Connect, PostgreSQL, Superset and AWS S3
mariaflix-serasa
marianafmedeiros.github.io
meu-repositorio-remoto
python-mastery
Advanced Python Mastery (course by @dabeaz)
quantstats
Portfolio analytics for quants, written in Python
react-todo
A simple todo app made with react
search-algo-a
First activity for the class: Cognitive and adaptive agents
service-course
spark-scala-examples
This project provides Apache Spark SQL, RDD, DataFrame and Dataset examples in Scala language
terraform-rony
vitrine-imersao-react
words-qty
This is a simple beginner project that, given a sequence of characters, the program returns all possible words made with them.
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