climatechange-ai-tutorials
Popular repositories Loading
-
nlp-policy-analysis
nlp-policy-analysis PublicExplore how Natural Language Processing (NLP) can be used to assist in identifying and mapping climate-relevant literature using a supervised learning approach and leverage a state of the art Large…
-
lulc-classification
lulc-classification PublicMapping the extent of land use and land cover categories over time is essential for better environmental monitoring, urban planning and nature protection. Train and fine-tune a deep learning model …
-
optimal-power-flow
optimal-power-flow PublicAC Optimal Power Flow (OPF) attempts to determine the setpoints of generators that would minimize the operating cost of a power system while meeting other operational constraints. In this tutorial,…
-
building-control-boptest
building-control-boptest PublicApply reinforcement learning to a building emulator to intelligently control HVAC systems.
-
climatelearn
climatelearn PublicApply machine learning to predict climate variables into the future and transform low-resolution outputs of climate models into high-resolution regional forecasts.
-
bioacoustic-monitoring
bioacoustic-monitoring PublicThis tutorial presents an "agile modeling" approach that enables users to build custom classifier systems efficiently for species of interest using transfer learning, audio search, and human-in-the…
Repositories
- visual-prompt-tuning-for-remote-sensing Public
One Prompt Fits All: Visual Prompt-Tuning for Remote Sensing Segmentation
climatechange-ai-tutorials/visual-prompt-tuning-for-remote-sensing’s past year of commit activity - tracking-ml-emissions Public
Learn how to measure a machine learning model's carbon footprint and practice strategies that can help shrink the energy involved in training these models.
climatechange-ai-tutorials/tracking-ml-emissions’s past year of commit activity - quantus-x-climate Public
In climate science, explainable artificial intelligence (XAI) can be used to improve and validate deep learning methods, but evaluation and selection of XAI methods is challenging. Learn how to use the explainable AI evaluation package Quantus to compare and select an appropriate XAI for your climate AI research task.
climatechange-ai-tutorials/quantus-x-climate’s past year of commit activity - lulc-classification Public
Mapping the extent of land use and land cover categories over time is essential for better environmental monitoring, urban planning and nature protection. Train and fine-tune a deep learning model to classify satellite images into 10 LULC categories.
climatechange-ai-tutorials/lulc-classification’s past year of commit activity - fourcastnet Public
Learn how to use FourCastNet, a weather model based on deep learning, to obtain short to medium-range forecasts of crucial atmospheric variables such as surface wind velocities.
climatechange-ai-tutorials/fourcastnet’s past year of commit activity - counterfactual-models-energy-saving Public
Using a real-world dataset of hourly meter and weather data, participants will learn to build a robust counterfactual energy baseline with a LightGBM (Gradient Boosting Machine) model.
climatechange-ai-tutorials/counterfactual-models-energy-saving’s past year of commit activity - camels-hydrological-modeling Public
A guide to model hydrological system using the real-world CAMELS dataset, which contains weather drivers for 531 basins across the continental United States. Through this modeling process, we will demonstrate various methods to predict streamflow, aiding in flood and drought planning.
climatechange-ai-tutorials/camels-hydrological-modeling’s past year of commit activity - aquaculture-mapping Public
Managing aquaculture ponds is vital for environmental monitoring and conservation. This tutorial presents how to leverage satellite imagery and semantic segmentation models to detect and map aquaculture ponds based on production intensity.
climatechange-ai-tutorials/aquaculture-mapping’s past year of commit activity - optimal-power-flow Public
AC Optimal Power Flow (OPF) attempts to determine the setpoints of generators that would minimize the operating cost of a power system while meeting other operational constraints. In this tutorial, learn how to leverage PyTorch to train a neural network to approximate the optimal solutions.
climatechange-ai-tutorials/optimal-power-flow’s past year of commit activity - piggy-cast Public
This tutorial introduces PiggyCast, an ensemble machine learning model designed to improve weather prediction accuracy by stacking forecasts from various numerical, AI-based, and hybrid weather prediction models.
climatechange-ai-tutorials/piggy-cast’s past year of commit activity
People
This organization has no public members. You must be a member to see who’s a part of this organization.
Top languages
Loading…
Most used topics
Loading…