awesome-earth-artificial-intelligence
github.com/esipfed/awesome-earth-artificial-intelligence ↗A curated list of Earth Science's Artificial Intelligence (AI) tutorials, notebooks, software, datasets, courses, books, video lectures and papers. Contributions most welcome.
Use this list with your AI agent
Add the Context Awesome MCP server to Claude, Cursor, or any MCP client, then ask:
"Show me thoughts resources from awesome-earth-artificial-intelligence"
Installation instructions →What's inside
Thoughts
- 37 reasons why your neural network is not working
- Artificial intelligence: A powerful paradigm for scientific research
- 'Farewell Convolutions' – ML Community Applauds Anonymous ICLR 2021 Paper That Uses Transformers for Image Recognition at Scale
- Learning earth system models from observations: machine learning or data assimilation?
- Why 90% of machine learning models never hit the market
Books
Papers
- Adoption of machine learning techniques in ecology and earth science
- Advancing AI for Earth Science: A Data Systems Perspective
- A Review of Earth Artificial Intelligence
- A Review of Practical AI for Remote Sensing in Earth Sciences
- Big Earth data analytics: A survey
- CIRA Guide To Custom Loss Functions For Neural Networks In Environmental Sciences - Version 1
Version 1
Tutorials
- AI Cheatsheets
Essential Cheat Sheets for deep learning and machine learning engineers. It contains a lot of useful tutorials to learn awesome tricks on AI engineering
- Artificial Intelligence in Earth science Book Materials
- ELSI-DL-Bootcamp
Intro to Machine Learning and Deep Learning for Earth-Life Sciences,
- EO-learn-workshop
EO-learn-workshop: Bridging Earth Observation data and Machine Learning in Python,
- GeoSMART Machine Learning Curriculum & Use Cases
- Machine Learning for Development
Courses
- American Meterological Survey AI Webinar Series
- Artificial Intelligence for Earth System Science (AI4ESS) Summer School
- Fundamentals of ML and DL in Python
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in python using Scikit-Learn and TensorFlow.
- GeoSMART Machine Learning Curriculum
- ICESat-2 Hackweek
- ML Seminar: Physics-informed Machine learning for weather and climate science
RelatedAwesome
Code
- BassNet
Deep Learning for Land-cover Classification in Hyperspectral Images,
- EarthEngine-Deep-Learning
Deep Learning on Google Earth Engine,
- Earth Lens
Earth Lens, a Microsoft Garage project is an iOS iPad application that helps people and organizations quickly identify and classify objects in aerial imagery through the power of machine learning.
- Earth System Emulator (ESEm)
A tool for emulating geophysical datasets including (but not limited to) Earth System Models
- EmissionAI
Microsoft AI for Earth Project: AI Monitoring Coal-fired Power Plant Emission from Space
- EQTransformer
An AI-Based Earthquake Signal Detector and Phase Picker.
Tools
- BentoML
BentoML is an open-source framework for high-performance ML model serving.
- Dopamine
- EarthML
- eo-learn
- flashflight:
flashflight: A C++ standalone library for machine learning.
- Global Forest Watch
ML-powered deforestation and forest cover change monitoring platform using satellite imagery analysis; provides near-real-time alerts used by researchers and conservation organizations globally.
Showing a sample of 102 resources. View the full list on GitHub →