Pinned Repositories
AI4G_mindmap
Mind map presenting an overview of the "Data Science and AI for good" movement
digitalgarden
Personal knowledge garden dedicated to AI, ML, AI for Earth Sciences, AI for good, Machine Learning and Data Science
dl4ds
Deep Learning for empirical DownScaling. Python package with state-of-the-art and novel deep learning algorithms for empirical/statistical downscaling of gridded data
ecubevis
Earth CUBE VISualization with Python. Intended for the interactive exploration of n-dimensional (2D, 3D, 4D or 5D) arrays on Jupyterlab
exoimaging_challenge_extras
Extra material for the Exoplanet Imaging Challenge
hciplot
Library for visualizing high-contrast imaging multidimensional datacubes on JupyterLab
sodinn
supervised-detection-exoplanets-hci
Code for paper: "Supervised detection of exoplanets in high-contrast imaging sequences", Gomez Gonzalez et al 2018
VIP_extras
Datacubes, Jupyter tutorials and other materials related to VIP (https://github.com/vortex-exoplanet/VIP)
VIP
VIP is a python package/library for angular, reference star and spectral differential imaging for exoplanet/disk detection through high-contrast imaging.
carlos-gg's Repositories
carlos-gg/dl4ds
Deep Learning for empirical DownScaling. Python package with state-of-the-art and novel deep learning algorithms for empirical/statistical downscaling of gridded data
carlos-gg/ecubevis
Earth CUBE VISualization with Python. Intended for the interactive exploration of n-dimensional (2D, 3D, 4D or 5D) arrays on Jupyterlab
carlos-gg/digitalgarden
Personal knowledge garden dedicated to AI, ML, AI for Earth Sciences, AI for good, Machine Learning and Data Science
carlos-gg/sodinn
carlos-gg/VIP_extras
Datacubes, Jupyter tutorials and other materials related to VIP (https://github.com/vortex-exoplanet/VIP)
carlos-gg/exoimaging_challenge_extras
Extra material for the Exoplanet Imaging Challenge
carlos-gg/hciplot
Library for visualizing high-contrast imaging multidimensional datacubes on JupyterLab
carlos-gg/supervised-detection-exoplanets-hci
Code for paper: "Supervised detection of exoplanets in high-contrast imaging sequences", Gomez Gonzalez et al 2018
carlos-gg/AI4G_mindmap
Mind map presenting an overview of the "Data Science and AI for good" movement
carlos-gg/ML_tests
Notebooks with various machine/deep learning experiments
carlos-gg/Sentinel-2-data-tests
A couple of hours exploring Sentinel-2 data during the RADA big data workshop (https://as595.github.io/RADABigData/)
carlos-gg/VIP
VIP is a package for angular, reference star and spectral differential imaging for high-contrast direct imaging of extra-solar planets and disks.
carlos-gg/2018-05-31-grenoble-software-carpentry
carlos-gg/astropy.github.com
The Astropy web pages
carlos-gg/carlos-gg.github.io
Personal website
carlos-gg/eo-learn
Earth observation processing framework for machine learning in Python
carlos-gg/exoimaging_challenge
Exoplanets direct imaging data challenge (old website)
carlos-gg/friendship-test
Tests for common proper motion to determine if a stellar/planetary "friend" is bound.
carlos-gg/hvplot
A high-level plotting API for pandas, dask, xarray, and networkx built on HoloViews
carlos-gg/medellin-2019
Workshop slides, projects and jupyter notebooks for the Medellin 2019 RADA Big Data Summer School
carlos-gg/minimal-mistakes
:triangular_ruler: A flexible two-column Jekyll theme. Perfect for personal sites, blogs, and portfolios hosted on GitHub or your own server.
carlos-gg/napari
napari: a fast, interactive, multi-dimensional image viewer for python
carlos-gg/planets-1
test repository for software-carpentry workshop @ grenoble
carlos-gg/PyAstrOFit
Python package dedicated to the planet orbit fitting using MCMC approach.
carlos-gg/PyConES-2018-data
All known documentation about PyConES2018 (Slides, PDF, Repos)
carlos-gg/pycones_2021_slides
carlos-gg/pystore
Fast data store for Pandas time-series data
carlos-gg/scrapy
Scrapy, a fast high-level web crawling & scraping framework for Python.
carlos-gg/tw5-mindmap-test
carlos-gg/webscraping_nlp_ml
Webscraping, NLP and ML project developed for the S2DS 2017 bootcamp