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weiguo Yu's Projects

catboost icon catboost

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

causalml icon causalml

Uplift modeling and causal inference with machine learning algorithms

dowhy icon dowhy

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

earthml icon earthml

Tools for working with machine learning in earth science

ee_bionet icon ee_bionet

The Google Earth Engine implementation of the BioNet algorithm to estimate biophysical parameters along with their uncertainties.

eemont icon eemont

A python package that extends Google Earth Engine.

elm icon elm

Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.

everyfield icon everyfield

Delineating agricultural field boundaries from Sentinel-2 imagery. Code from Jesse Bakker's MA thesis project, University of Minnesota Department of Geography, Environment and Society..

field-delineation icon field-delineation

Field delineation with Sentinel-2 data from Sentinel-Hub and a ResUnet-a architecture.

fieldrnn icon fieldrnn

Temporal Vegetation Classification with Recurrent Neural Networks

gee_s1_ard icon gee_s1_ard

Creates an analysis ready sentinel-1 SAR image collection in Google Earth Engine by applying additional border noise correction, speckle filtering and radiometric terrain normalization.

geemap icon geemap

A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and ipywidgets

geet icon geet

Google Earth Engine Toolbox - Library to write small EE apps or big/complex apps with a lot less code.

geoda icon geoda

GeoDa: An introduction to spatial data analysis

globalc icon globalc

A topdown and bottom up approach for global C cycle

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