- London
Stars
Slides and code samples for training, tutorials, and workshops about Docker, containers, and Kubernetes.
Supplementary material for our paper "THERE IS NO DATA LIKE MORE DATA" is provided.
Repository for Digital Earth Africa Sandbox, including: Jupyter notebooks, scripts, tools and workflows for geospatial analysis with Open Data Cube and xarray
Techniques for deep learning with satellite & aerial imagery
A sample project that exists for PyPUG's "Tutorial on Packaging and Distributing Projects"
Reads key-value pairs from a .env file and can set them as environment variables. It helps in developing applications following the 12-factor principles.
Solutions of the exercises and problems from Michael Nielsen's book Neural Networks and Deep Learning: http://neuralnetworksanddeeplearning.com/
Deep Learning Illustrated (2020)
Generic U-Net Tensorflow 2 implementation for semantic segmentation
interactive visualization of 5 popular gradient descent methods with step-by-step illustration and hyperparameter tuning UI
Machine Learning for Earth Observation Training of Trainers Bootcamp
Helper package with multiple U-Net implementations in Keras as well as useful utility tools helpful when working with image semantic segmentation tasks. This library and underlying tools come from …
Labs and demos for courses for GCP Training (http://cloud.google.com/training).
A repository of custom scripts to be used with Sentinel Hub
This repository contains a Jupyter Notebook for automatic flood extent mapping using space-based information.
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
Semantic segmentation on aerial and satellite imagery. Extracts features such as: buildings, parking lots, roads, water, clouds
🛰️ List of satellite image training datasets with annotations for computer vision and deep learning
The fastai book, published as Jupyter Notebooks
Python scripts for the textbook "Image Analysis, Classification and Change Detection in Remote Sensing, Fourth Revised Edition"
A curated list of awesome Synthetic Aperture Radar (SAR) software, libraries, and resources.
A curated list of awesome tools, tutorials, code, projects, links, stuff about Earth Observation, Geospatial Satellite Imagery
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.
Manipulation and analysis of geometric objects
GDAL is an open source MIT licensed translator library for raster and vector geospatial data formats.