rifatsdas Goto Github PK
Name: Rifat
Type: User
Company: Sensor Aktor GmbH
Bio: Full Stack Geospatial AI Engineer, Data science & Engineering, Algorithm dev., Web-app dev., Data cloud & Cloud computing.
Location: Darmstadt, Hessen, Germany
Rifat's Projects
py_spectral_index
This a repository of numbers of spectral index for remote sensing studies. All of the available spectral indexes are coded in python.
pythondatasciencehandbook
Python Data Science Handbook: full text in Jupyter Notebooks
pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
pywin32
Python for Windows (pywin32) Extensions
qgis
QGIS is a free, open source, cross platform (lin/win/mac) geographical information system (GIS)
qgis-earthengine-examples
A collection of 300+ Python examples for using Google Earth Engine in QGIS
qgis-processing
Example scripts, algorithms etc
raster-analysis-plotting
Example jupyter notebooks for multiband raster data analysis
rasterio
Rasterio reads and writes geospatial raster datasets
rifatsdas.github.io
My github user website
s1tbx
The Sentinel-1 Toolbox
s2tbx
Sentinel 2 Toolbox (s2tbx)
s3tbx
A toolbox for the OLCI and SLSTR instruments on board of ESA's Sentinel-3 satellite
s3tbx-scape-m
Atmospheric correction with the SCAPE-M algorithm
salib
Sensitivity Analysis Library in Python (Numpy). Contains Sobol, Morris, Fractional Factorial and FAST methods.
satellite_machine_learning
Unsupervised and supervised learning for satellite image classification
satellite_optical_indices
Mostly used optical indices with satellite images for studying earth surface and different features and their changes in spatio-temporal scale.
scikit-learn
scikit-learn: machine learning in Python
scipy
Scipy library main repository
scipy-cookbook
Scipy Cookbook
scope
SCOPE is a simulation model for radiative transfer, photosynthesis and energy fluxes in vegetation and soil.
sensitivity
:exclamation: This is a read-only mirror of the CRAN R package repository. sensitivity — Global Sensitivity Analysis of Model Outputs
somo
#SBHACK19
spyder
Official repository for Spyder - The Scientific PYthon Development EnviRonment
t81_558_deep_learning
Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks
tensorflow
Computation using data flow graphs for scalable machine learning
tethysapp-postgis_app
Solution for video tutorial: https://www.youtube.com/watch?v=YFnqySsZ4_Y
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