Stars
The official home of climt, a Python based climate modelling toolkit.
Python assignments for the machine learning class by andrew ng on coursera with complete submission for grading capability and re-written instructions.
the first library to let you embed a developer agent in your own app!
Simplifying the discovery and usage of machine-learning ready datasets in materials science and chemistry
eScience Institute supports hackweeks for community education and collaboration
The 🌏 data science library you've been waiting for~
TorchGeo: datasets, samplers, transforms, and pre-trained models for geospatial data
Examples of using the Planetary Computer
A tile map showing a month of streamflow conditions across the U.S.
A latent text-to-image diffusion model
A library to inspect and extract intermediate layers of PyTorch models.
Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)
Course material for the lecture "Differential equations in the earth system" (WS 2019/2020) @ CAU Kiel
IPython notebooks with demo code intended as a companion to the book "Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control" by Steven L. Brunton and J. Nathan Kutz
Machine learning to better predict and understand drought. Moving github.com/ml-clim
sbi is a Python package for simulation-based inference, designed to meet the needs of both researchers and practitioners. Whether you need fine-grained control or an easy-to-use interface, sbi has …
The Machine Learning & Deep Learning Compendium was a list of references in my private & single document, which I curated in order to expand my knowledge, it is now an open knowledge-sharing projec…
A library for scientific machine learning and physics-informed learning
Learning in infinite dimension with neural operators.
This is the repository for the distill web framework
Differentiable SDE solvers with GPU support and efficient sensitivity analysis.
You can operate Windows with key bindings like Vim.
Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)
Arduino library for Internet of Things Rapid Prototyping in environmental sensing
High-Performance Symbolic Regression in Python and Julia
Python library to train neural networks with a strong focus on hydrological applications.