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machine_learning_clouds_and_satellite_images

machine_learning_engineering_nanodegree

medium

for medium articles

metpy

A Python Package for Meteorological Data

mkmov

python movie maker for NetCDF files

multi-temporal-super-resolution

Multi-temporal Super-Resolution on Sentinel-2 Imagery using Deimos

my_app

netcdf_mpi

This "C" code will read the NetCDF file format (Ex. WRF output files). The MPI code will fork the processes based on time dimension of the data over each node in order to make data processing fast.

openagro-precision-agriculture-with-drones-

Set of Machine Learning Algorithms developed with the aim of determining health states of different types of crops

plotting_wrf_netcdf

probabilistic-programming-and-bayesian-methods-for-hackers

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

pyextremes

Extreme Value Analysis (EVA) in Python

python-lists-lab-data-science-intro-000

python-practical-application-on-climate-variability-studies

This tutorial is a companion volume of Matlab versionm but add more. Main objective is the transference of know-how in practical applications and management of statistical tools commonly used to explore meteorological time series, focusing on applications to study issues related with the climate variability and climate change. This tutorial starts with some basic statistic for time series analysis as estimation of means, anomalies, standard deviation, correlations, arriving the estimation of particular climate indexes (Niño 3), detrending single time series and decomposition of time series, filtering, interpolation of climate variables on regular or irregular grids, leading modes of climate variability (EOF or HHT), signal processing in the climate system (spectral and wavelet analysis). In addition, this tutorial also deals with different data formats such as CSV, NetCDF, Binary, and matlab'mat, etc. It is assumed that you have basic knowledge and understanding of statistics and Python.

python-variables-lab-data-science-intro-000

python-variables-readme-data-science-intro-000

pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

s2-superresolution

Deep Learning-based algorithm to upsample all Sentinel-2 bands to 10m. Also an example how to use GPUs on UP42.

sask_tourist

sbck

scientific-python-lectures

Lectures on scientific computing with python, as IPython notebooks.

semaphore-demo-php-unsplash

Image Gallery Demo for Unsplash in PHP and Laravel.

stock_analysis

storm_forecast

Storm intensity forecasting using machine learning and RAMP distributed high computing environments

toe_tools

Time of Emergence toolbox

twitter_emotion

upper_atmosphere_dashboard

water

An auto machine learning for internet of things related to water systems.

water-observatory-backend

Monitoring water levels of lakes and reservoirs using satellite imagery

waternet

A convolutional neural network that identifies water in satellite images.