Modeling Population Dynamics with AI: Hands-On Workshop with Population Dynamics Foundation Model
36Explore the transformative potential of the Population Dynamics Foundation Model (PDFM), a cutting-edge AI model designed to capture complex, multidimensional interactions among human behaviors, environmental factors, and local contexts. This workshop provides an in-depth introduction to PDFM Embeddings and their applications in geospatial analysis, public health, and socioeconomic modeling.
Participants will gain hands-on experience with PDFM Embeddings to perform advanced geospatial predictions and analyses while ensuring privacy through the use of aggregated data. Key components of the workshop include:
Introduction to PDFM Embeddings: Delve into the model architecture of PDFM and discover how aggregated data (such as search trends, busyness levels, and weather conditions) generates location-specific embeddings.
Data Preparation: Learn to integrate ground truth data, including health statistics and socioeconomic indicators, with PDFM Embeddings at the postal code or county level.
Hands-On Exercises: Engage with interactive Colab notebooks to explore real-world applications, such as predicting housing prices using Zillow data and nighttime light predictions with Google Earth Engine data.
Visualization and Interpretation: Analyze and visualize geospatial predictions and PDFM features in 3D, enhancing your ability to interpret complex datasets.
By the end of this workshop, participants will have a strong foundation in utilizing PDFM Embeddings to address real-world geospatial challenges.
Target Audience:
This workshop is designed for data scientists, geospatial analysts, researchers, urban planners, and professionals in public health, economics, or environmental science who want to integrate AI into their workflows.
Prerequisites:
A Google Colab account.
Access to the PDFM embeddings.
Basic understanding of Python programming and geospatial data concepts is recommended.
Duration:
1.5 hours (including interactive exercises, demos, and Q&A sessions)
Speaker
Qiusheng Wu
Moderator:
Rohini: https://aiforgood.itu.int/speaker/rohini-swaminathan/
Maria: https://aiforgood.itu.int/speaker/maria-antonia-brovelli/
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