Ciaran1981's Stars
shap/shap
A game theoretic approach to explain the output of any machine learning model.
kmario23/deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
interpretml/interpret
Fit interpretable models. Explain blackbox machine learning.
DistrictDataLabs/yellowbrick
Visual analysis and diagnostic tools to facilitate machine learning model selection.
UX-Decoder/Segment-Everything-Everywhere-All-At-Once
[NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"
opengeos/segment-geospatial
A Python package for segmenting geospatial data with the Segment Anything Model (SAM)
GeostatsGuy/PythonNumericalDemos
Well-documented Python demonstrations for spatial data analytics, geostatistical and machine learning to support my courses.
skrub-data/skrub
Prepping tables for machine learning
GeoStat-Framework/PyKrige
Kriging Toolkit for Python
cerlymarco/shap-hypetune
A python package for simultaneous Hyperparameters Tuning and Features Selection for Gradient Boosting Models.
linkedin/FastTreeSHAP
Fast SHAP value computation for interpreting tree-based models
pysal/momepy
Urban Morphology Measuring Toolkit
geopython/OWSLib
OWSLib is a Python package for client programming with Open Geospatial Consortium (OGC) web service (hence OWS) interface standards, and their related content models.
eli5-org/eli5
A library for debugging/inspecting machine learning classifiers and explaining their predictions
isciences/exactextract
Fast and accurate raster zonal statistics
corentin-dfg/Satellite-Image-Time-Series-Datasets
This page presents a list of satellite imagery datasets with a temporal dimension, mainly satellite image time series (SITS) and satellite videos, for various computer vision and deep learning tasks. It covers multi-temporal datasets with more than two acquisitions but not bi-temporal datasets.
maja601/EuroCrops
The official repository for the EuroCrops dataset.
IGNF/myria3d
Myria3D: Aerial Lidar HD Semantic Segmentation with Deep Learning
r-barnes/ArcRasterRescue
Extract raster data from ArcGIS/ESRI formats
leftfield-geospatial/geedim
Search, composite, and download Google Earth Engine imagery.
Living-with-machines/MapReader
A computer vision pipeline for exploring and analyzing images at scale
Akramz/end-to-end-gee
Reproducing the "End-to-End Google Earth Engine" course using Jupyter Notebooks and geemap.
Doodleverse/segmentation_gym
A neural gym for training deep learning models to carry out geoscientific image segmentation. Works best with labels generated using https://github.com/Doodleverse/dash_doodler
guiwitz/naparimovie
Create movies from series of key-frames in napari.
SmartForest-no/Point2tree
dsgibbons/shap
A game theoretic approach to explain the output of any machine learning model.
doruk-oner/TOPO-Windowed-Loss
jasperroebroek/sklearn-quantile
cod3licious/ml_exercises
Python Exercises for my Machine Learning Course
gro5-AberUni/RegionGrow
Qgis Region Growing Plugin