/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.

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Awesome-Earth-Artificial-Intelligence

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A curated list of tutorials, notebooks, software, datasets, courses, books, video lectures and papers specifically for Artificial Intelligence (AI) use cases in Earth Science.

Maintained by ESIP Machine Learning Cluster. Free and open to inspire AI for Good.

Contributions are most welcome. Please refer to our contributing guidelines, what is awesome?, and Code of Conduct.

Contents

Courses Books Tools Tutorials Training Datasets
Code Videos Journals Reports RelatedAwesome
Competitions Newsletters Communities RelatedAwesome

ML-enthusiastic Earth Scientific Questions

Earth Spheres Scientific Problems
Geosphere
  • How to identify hidden signals of earthquakes?
  • How to learn the spatio-temporal relationships amonog earthquakes and make predictions based on the relationship?
  • How to capture complex relationships of volcano-seismic data and classify explosion quakes in volcanos?
  • How to predict landslides
  • How to estimate the damage?
Atmosphere
  • How to trace and predict climate change using machine learning?
  • How to predict hurricane?
  • How to monitor and predict meteorological drought?
  • How to detect wildfire early?
  • How to monitor and predict air quality?
  • How to predict dust storm?
Hydrosphere
  • How to do high spatio-temporal resoluton waterbody mapping?
  • How to get insights of water quality from remote sensing?
  • How to monitor, and predict snow melt as a water resource?
Biosphere
  • How to do high spatio-temporal resoluton forest mapping?
  • How to do high spatio-temporal resoluton crop mapping?
  • How to do high spatio-temporal resoluton animal mapping?
Cryosphere
  • How to do high spatio-temporal resoluton mapping and classification of sea ice?
  • How to monitor and predict glacier/ice sheet mass loss?

Courses

Books

Tools

  • eo-learn: Earth observation processing framework for machine learning in Python,

  • EarthML website: Tools for working with machine learning in earth science,

  • ML visualization tool - A Visualization tool for neural network, deep learning and machine learning models, support ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Core ML (.mlmodel), Caffe (.caffemodel, .prototxt), Caffe2 (predict_net.pb), Darknet (.cfg), MXNet (.model, -symbol.json), Barracuda (.nn), ncnn (.param), Tengine (.tmfile), TNN (.tnnproto), UFF (.uff) and TensorFlow Lite (.tflite).

  • Dopamine is a research framework for fast prototyping of reinforcement learning algorithms,

  • mlflow - MLflow: A Machine Learning Lifecycle Platform,

  • Snips NLU Snips NLU (Natural Language Understanding) is a Python library that allows to extract structured information from sentences written in natural language.

  • MindsDB - MindsDB is an Explainable AutoML framework for developers built on top of Pytorch. It enables you to build, train and test state of the art ML models in as simple as one line of code.

  • TensorFlow Hub TensorFlow Hub is a repository of reusable assets for machine learning with TensorFlow. In particular, it provides pre-trained SavedModels that can be reused to solve new tasks with less training time and less training data.

  • Polyaxon - Polyaxon, a platform for building, training, and monitoring large scale deep learning applications. A Machine Learning Platform for Kubernetes.

  • MMLSpark - MMLSpark is an ecosystem of tools aimed towards expanding the distributed computing framework Apache Spark in several new directions. Microsoft Machine Learning for Apache Spark,

  • TransmogrifAI - TransmogrifAI (pronounced trăns-mŏgˈrə-fī) is an AutoML library written in Scala that runs on top of Apache Spark. It was developed with a focus on accelerating machine learning developer productivity through machine learning automation, and an API that enforces compile-time type-safety, modularity, and reuse.

  • Microsoft AI for Earth API Platform - Microsoft AI for Earth API Platform is a distributed infrastructure designed to provide a secure, scalable, and customizable API hosting, designed to handle the needs of long-running/asynchronous machine learning model inference. It is based on Azure and Kubernetes.

  • OneFlow - OneFlow is a performance-centered and open-source deep learning framework.

  • ml.js - ml.js - Machine learning tools in JavaScript.

  • BentoML - BentoML is an open-source framework for high-performance ML model serving.

  • flashflight: - flashflight: A C++ standalone library for machine learning.

Tutorials

Training Data

Code

Videos

Journals

Reports

Thoughts

Competitions

Newsletters

Communities

RelatedAwesome

  • Awesome-Open-GeoscienceAwesome A list is curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome. In accordance with the awesome manifesto, we add awesome repositories.
  • Awesome-SpatialAwesome Awesome list for geospatial, not specific to geoscience but significant overlap
  • Awesome Open Climate ScienceAwesome Awesome list for atmospheric, ocean, climate, and hydrologic science
  • Awesome CoastalAwesome Awesome list for coastal engineers and scientists
  • Awesome Satellite Imagery Datasets - Awesome List of aerial and satellite imagery datasets with annotations for computer vision and deep learning