asiya-z

asiya-z

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asiya-z's repositories

eo-learn

Earth observation processing framework for machine learning in Python

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intro-terra-ecodatascience

Introduction to using the R package terra for raster spatial data manipulation

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handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

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scalable-computing-examples

Companion repository for examples from the scalable-computing-course

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deep-learning-for-earth-observation

Application of deep learning for earth observation.

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R_test

test of course R feb 2024

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dplyr

dplyr: A grammar of data manipulation

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ml-course-hse

Машинное обучение на ФКН ВШЭ

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ml-course

Open Machine Learning course

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Deep_learning_school

Решения домашних заданий продвинутого потока курса "Deep Learning" Школы глубокого обучения ФПМИ МФТИ

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website2022

ICESat-2 Hackweek 2022 landing page and jupyter book

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LT-GEE

Google Earth Engine implementation of the LandTrendr spectral-temporal segmentation algorithm. For documentation see:

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dvm-dos-tem

A process based Dynamic Vegetation, Dynamic Organic Soil, Terrestrial Ecosystem Model.

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geemap

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

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NSIDC-Data-Tutorials

Jupyter notebook-based tutorials to learn how to access and work with select NSIDC DAAC data.

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wesanderson

A Wes Anderson color palette for R

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workshops

Online material for various workshops

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GDAL_OGR_Python_Workshop_2021

Репозиторий для мастер-класса по базовому использованию GDAL/OGR в Python для #спбгеотех

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earthengine-api

Python and JavaScript bindings for calling the Earth Engine API.

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Spatial-R-PhD-course

Data and information for GGBC PhD course in spatial analyses in R

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ai2es_xai_course

Notebooks for AI2ES (NSF Institute for Research on Trustworthy Artificial Intelligence in Weather, Climate, and Coastal Oceanography) short course on XAI (explainable artificial intelligence).

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pythonhse

Программирование на языке Python для сбора и анализа данных (НИУ ВШЭ)

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