eluisluzquadros
Ph.D. Candidate | Earth Scientist | GeoAi | Climate Risk
PUCRSPorto Alegre, Rio Grande do Sul, Brasil
Pinned Repositories
2018
Course materials for the 2018 version of the Automating GIS processes -course at the University of Helsinki, Finland
approachingalmost
Approaching (Almost) Any Machine Learning Problem
AutomatedStockTrading-DeepQ-Learning
Every day, millions of traders around the world are trying to make money by trading stocks. These days, physical traders are also being replaced by automated trading robots. Algorithmic trading market has experienced significant growth rate and large number of firms are using it. I have tried to build a Deep Q-learning reinforcement agent model to do automated stock trading.
Automating-GIS-processes-2016
GitHub Pages for Automating GIS-processes
autoscraper
A Smart, Automatic, Fast and Lightweight Web Scraper for Python
book
This book serves as an introduction to a whole new way of thinking systematically about geographic data, using geographical analysis and computation to unlock new insights hidden within data.
COVID-Kunumi-42
Repositório com o material utilizado no WorkShop 42+Kunumi sobre aplicações de ML
Kunumi_Workshop_Covid19
openaddresses
A repository of global open address data.
pyro
Deep universal probabilistic programming with Python and PyTorch
eluisluzquadros's Repositories
eluisluzquadros/COVID-Kunumi-42
Repositório com o material utilizado no WorkShop 42+Kunumi sobre aplicações de ML
eluisluzquadros/Kunumi_Workshop_Covid19
eluisluzquadros/pyro
Deep universal probabilistic programming with Python and PyTorch
eluisluzquadros/approachingalmost
Approaching (Almost) Any Machine Learning Problem
eluisluzquadros/autoscraper
A Smart, Automatic, Fast and Lightweight Web Scraper for Python
eluisluzquadros/book
This book serves as an introduction to a whole new way of thinking systematically about geographic data, using geographical analysis and computation to unlock new insights hidden within data.
eluisluzquadros/build-your-own-radar
A library that generates an interactive radar, inspired by http://thoughtworks.com/radar/
eluisluzquadros/CAR
eluisluzquadros/Complete-Life-Cycle-of-a-Data-Science-Project
Complete-Life-Cycle-of-a-Data-Science-Project
eluisluzquadros/covid-20
A collection of work related to COVID-19
eluisluzquadros/covid-impact-scrapper
eluisluzquadros/covid_impact_se
eluisluzquadros/dataprep
DataPrep — The easiest way to prepare data in Python
eluisluzquadros/duckdb_h3
eluisluzquadros/eemont
A python package that extends Google Earth Engine.
eluisluzquadros/flow-forecast
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
eluisluzquadros/Google2Csv
Google2Csv a simple google scraper that saves the results on a csv/xlsx/jsonl file
eluisluzquadros/GoogleSpider
This is the repo for my tutorial Crawling Google Search Results on dev.to.
eluisluzquadros/gym
A toolkit for developing and comparing reinforcement learning algorithms.
eluisluzquadros/h3-py-notebooks
Jupyter notebooks for h3-py, a hierarchical hexagonal geospatial indexing system
eluisluzquadros/hybridSE
eluisluzquadros/if977
Repositório da disciplina de Engenharia de Software voltada ao curso de Sistemas de Informação.
eluisluzquadros/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
eluisluzquadros/MachineHack
eluisluzquadros/MapBiomas_collection6
MapBiomas collection6
eluisluzquadros/ML-covid
Workshop Kunumi-42 envolvendo machine learning para determinar casos de covid através de exames laboratoriais
eluisluzquadros/notebook-emerging-topics-corpora
Jupyter notebooks to work with text corpora to identify trends in text.
eluisluzquadros/odc-colab
eluisluzquadros/pints
Probabilistic Inference on Noisy Time Series
eluisluzquadros/SICAR
This tool is designed for students, researchers, data scientists or anyone who would like to have access to SICAR files