climatechange-ai-tutorials
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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…
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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 …
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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,…
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building-control-boptest
building-control-boptest PublicApply reinforcement learning to a building emulator to intelligently control HVAC systems.
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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.
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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
- 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.
- mobility-demand Public
Ensuring a shared bike is readily available can reduce demand for less climate-friendly transportation options. Explore how to model the relationship between bike usage and points of interest (POIs) to identify the best locations for new shared-bike stands.
- 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.
- citylearn Public
Learn how to design simple and advanced control algorithms to provide energy flexibility, and acquire familiarity with the CityLearn environment and its datasets for extended use in projects. The tutorial provides a walk-through on how to set up and interact with the environment using a real-world dataset in three hands-on control experiments.
- agricultural-monitoring-ftw Public
This tutorial demonstrates how to generate field boundaries globally using the Fields of The World dataset, pretrained models, and command line interface (CLI). We then show how to use those boundaries in agricultural monitoring tasks under climate change, including crop type classification and forest loss monitoring.
- intro-ai-tsunami-alerts Public
Introduction to AI - Predicting Tsunami Alerts from Earthquake Observations
- nlp-policy-analysis Public
Explore 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 Language Model (LLM) to classify climate policy documents.
- downscaling-climate-projections Public
Statistical Downscaling of Climate Projections with Deep Learning
- visual-prompt-tuning-for-remote-sensing Public
One Prompt Fits All: Visual Prompt-Tuning for Remote Sensing Segmentation
- 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.
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